{"type":"session","version":3,"id":"2f9c5b1e-8a95-4ea4-80b6-03b88d88c1cb","timestamp":"2026-04-11T21:06:28.893Z","cwd":"/home/alex/.pi/agent/skills/frontend"}
{"type":"agent_start"}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"user","content":[{"type":"text","text":"IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ..."}],"timestamp":1775941589168}}
{"type":"message_end","message":{"role":"user","content":[{"type":"text","text":"IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ..."}],"timestamp":1775941589168}}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_end","contentIndex":0,"content":"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"1Xk2XWqR1ulgVF+AJkO7BUV5tbcFP1HuDrMrWoBVApM5IFGnqmsLcHNq51N9dBQxVXpshYmeu3qdsIl4P7G5ghwhWc3/LFTU1jQPKXsshquHEFL5sZdComr71OFNboxQj8KCDd7D7pOHyLXrAvbkB9uvkiLhNNDEKCaY2fVg/EIH0KoVCW0H4ARW+EeiUT/1JJxQZSBu3yTZaf6fYHCGwJ9vBRvcA+iTaU+uQByldbXAq6gp0Sx5khPwgbPPrY/+12fnjEOoaiL4CtL829A8ME3ffE9Y36yUZS95pR0lwAmtScxNbOZQAVkDvNK3wTDjA8E/sM3LkJzs+gM7SOkbDyJMxm9EGfIMXCgDd4ecmbo9690EeeHUR1aZO8DiJRLm3c6Q2n+U9zvLWLoWLpLJrVSGqvfPy1GFwvDbzkI6RFAPHDyEwn5kzss3JV8vyVpOAdNADVcff4PHnraAfMiLnzVbD82VgRHvr8IiAn9xdwW0OwwFs2mFZJqMoDjtsRjfiR+XdrRO/NQJsUNKA253IvZeTC9cou5htZbNHSB/VEKhu8DlZTDzYfzAHRyrg9wz/TaovEwAmVaiEQungMBPNoXVLAiQYptwF/ZFo87rpOOCu31nm5mtRuSnf6G/hXGsnMkvG47WheiNcqvGLYsKzi74tY/sx2u944zKL3diUsFPuA4RpIJUCO37XrtxLsErb/3AtzmNTkKRef3++iMPPeysq5SGbGAIBbKIak0R8dYS6bmZ6gRjM8Cm7eJ5VFrfeSmocmur3pG9zipACIDwVXMHh80OjRVL6fmgKfSJ9sv3ey+nnkmAyC1yXx00CFbrTLvWgIBwIHd00ArmSJF9vhdjCTRjj1bOml4WgDFAS6TFcNiB9+hdzNYnAoeSWg+RwVtg11oNLiAW/NXYRzUXUN1GMPrNnhpT1ut6if5w0gbsZbBgtJCJeM1ZTRwWz3caL3MPtNhJ/40cSYLcAzVjIkWl8fUnYyilfbKa7QQVcvAoFOH2Z6L6L4xaFc3miJOcidB0Aj2/Opal03hMmi87LKVy8Aas58fphWB9pBgyiLBB/WISf1CzX3Lzqtt4GqxLz0lSfpz434fcCn5O54Zwhvs8c9+7JTfB806NB726KvvkHie23j+0V8N+pR/NclxYpXXocA/UFZ43LWaSfb/31vH7c5IpxMrAQyEg7Gq2Fg3EaEZeRiAsFrgUFM6vwPlLAqeEFC1cYqlXzme/pwzo2XlIPJWFgL0R8w+sxctVd7c9OO7ETU2P7uhjjyfiCR8KKadzJodSE7Tu5ZcQ8glIuRR4GB7b/bHiuvtcCusoo/YUyvuHCuLRVHFfdP9hmkqSqXlnHVs/zF0z9FUAkh/8phGbl+Wm91CeyHYYedS2net2C4gBfTqcXhC23YIly8W8yJw8Mk+OJ/JGpk1h2R0GAaRn90rMKWf4sGEHvpzNS0QmE7QbdnN9npCCqq+HTzjzfxMGLKxXCaLg7bsijh4dsyM5XEVJPmEC/2RDTUzPGkDoaUtH9UJLlS0cGVgm2wGKvOPOn30mtdm6FY9Nr4Ppeb7Z+JYntP5uXhQ9II+e9U/BDyHeDiM8Ic00Yl6rrQo+yHmTyaPo0gNNn6+hUad6dHNskssXGYpFyc+qvlIm6AzgwnZWJQxUFwg4i763uv2lmVbheLLaKa2GGHmBngznXc7KxyOWOAQeipN640Wvzecx0Ta94YDYoSWpnDZwY71T9GA5d8PXEALESsDE5fp9Rzx8MnlTWjRx/+lj0AqxN6Jo89PtPBMu79i9zOag9CbVQ7E6kZv3xaJwT/L8WafMaY6wgSSCvDP+gKvAWSllDqGnAuqQJPYGfQookfh12u5izJMOsbi7fTQLIi0s+wiPIDHRlgIXjdjnwBk7mrk/j26veLHrqu0ZfGD4Hm6O/e4TX9LjAmzMMjoHMZ7UBIhimMVqMYxOaTWBs7dMUTy8dBYMOr8ijXd7/He2dY9Z8eoOEfL0zQw9QVIkXwvM8uSUUMj3YH9CjTM/cx4NC8ZopnoP7CIKJitQhu/4opvV6XeqbudQ46afPdW4Eob5hILE44oPoxuzT1R7XuySHHr5WffrnLe0RrQ9bCtrKctsM14cvlaYzyy+UhZ8lFX5vTnvHlTdhrieMvQE7qunpEl1Kl/OFDfj7Oy4c3sVSU2kbl6XUeBjjgw3cU4l7w4bZFNP0DjYw6cwTy1XDm+DSEb9CvZ25cyKqoRkJwKkZYzL+ieKTX9luO4CHZxCG2KxtlXHA3GJ4meDX5cMO/91xkAC250JL7R307u+/Ez+QjsnFkoj2fn/i/WEWe4KJ/BeMucUm/eFpOxDyYDv6J5ASyZJIV+pl6wFuAcKlDxnXUEuZ3/ukeScQ0s78vttJVI56QEBBtF6qmOdll5jg+zPoMrUL8uDprMfueY3BBDixFQhoHdcMNfwXxpNZ8SZlnnonv+vqRF/Kuogebvn9JL0yIdtP4vG5f5IpPwe8K1iX8iqkhRUefa5NwDtiyU1D95p53tH8ou/hXGw72548mHNBeLx74a22YWYYcTLDjK8yVrMNB2rt8OJFvozORrqvSVNJcvaphxs60LVEcE2NWkwYtRsNtKH88MoJJ5VpxOIxpjjn/qdcYvvbujIdqYdzE0yWXvzN4rRpsImnbwaC3o+88fcXd/x4VDf8REZm9WnkFrFPNh0G0osMGBUP72a2rPqYqygBKwZlazuwGn0o0EO9kl05Hu9MyfR06LW/4AuMMBbxf2wNFXYOMtyB82tOn8MKBOTTUaOoSRALjhVE+qwRvpXVGYfLasIu2KSoH2GLADdpVuMt7uPkSkNWbO3XdSVRS4Dmr40aGR+0d2YfoG/kYizxRFgh6owofE6pfTQt+bDGrPwISRfY90qfFb2ZVCq2nFNDXLjh0MrSc7eFK1e90roUc3VNlhF5FiwXxUFdCGYX2JpDPk1ycaOYX5mSqe9FG19kDZgG7i0Mw1cK9/HqM77z0/eZfNSjPaDKvgLCDsdkvhS/I2u35e64L9nzQgGW1Icv4cCx2G1AD4A1gCmpObNgWA24TqN4NIZH/L/vYrgnEMEPX96HtPlTna2j0Qmo7UIczFk4/DmhiOLHHLYLpV0CamruvlAba+/UWi8AV96YUHn+Q5CRh3KkTc7cUm0vmCXLtUJ26Ws1XS0GEbvig7bLGjFqk5x6JRYY7mMVb+Ypa98gFwiHAJjqcVDcqiiYd5JPtGeR8zozTBtTunfH35V/II3vtSqT5QFdkXaTjXkJxcnLPcLgCzLpjJTjifKdfhvMkSEist43oown+fotZ+DCKE5zAIkS54d1btr6fVIcunM8I7weM5O4Aa+Yy2sSsmKTJGT9vCYlWn+eErDDW/LYJ+bvfTqPYC5ZCywMK+Qa4QlhgZTeKN4hFk27pkaOAVRZuP9TYuw4cfHHzwUrw1e6FN7yRIOyMx+rjIdnXcQ+47Ot3WXBzAF+7KtdSzpu/I0vtTbmQV1Qv8ftvEI5Kqd3pGrXAFsFVxQEbdSJcOYu0zB8ZNnfbfUWVyFrLQ+zWuZlTGrHblDWa/m53i6q4wAr+55kYPz1u5Yc/kS4DSCIq4yHejsFk/DlZP6ls3Ov5KGzUbYlbIEhCsBJ+AsR9WrsHBvcEzqLudCnX/KQ313lZpqN+lQNGk4nWMpy3v1L+LZayfwVcHtRdm7QrGAxc+wz3hPfdRgOP5fBU31V2bXoJRgTEju/2dprkac7hj9hHS+7GYe8BFVq3ZKywUYhYb0s66yF0a1TtW6cfJMOFuBvgNsU4Q4s3QlyD/JsvnhCBKHspoGJ64qebmeh13CCYzcQNnSb6LrUDH7gXc3abAi1iQ1s3gwnpvzcV+aObtIpY5lNsCSQ++gLJPkXukytj8/DgKWrwD0kuC270p5Ze7dZUotQSGXueoGyV85Pdu6OqBuVEYRu8xkfgnJ8iu5OpnsJb097lp7+G0EYLryxwWDlJZI8AfT/ySE+lQeSmw5OKD1Hk6goBZu5EGX6czZ7GLD94q8jMaV7aNe8XX7VLOWbLgUeV3hq7mPAmn7Sd1+ACaaUsyDezSnLOLbDjK9/xyFHObP51Yx1u0P3fDpaItF2iRkivBgyGdtzQ8h+2tHIFaa2czJ0RiW10hwskih2XEGDpZGWUScy000p8Cw7+tS5/OAwn2e5w33SP3+AEN0A8l4bC1wts/s36pMY+FifsXVryqU8CBJWvmFMtzBF2nEOkjx6JmhkuxOeuJkO+TSkZu2PLLSGgcg9qBCrYqqn03+0woBeOHH7EsF4LpMAddrsPdq+8J0p6e+ALsuZoohck7hH33t5H4ORp0AZPlMlguJZ5vkqwdWUXAnZTXloZWVLfBVdv1omNV/lZjA9+MOK576HOo/gBhYDzZgnl4JaIfeEXDnAA9uSZuoddoFcns/UhasTqwgeCKcckVWsB9ba0d/cCT49uazLQ+aSumLsxy/oTJz9QosQMtWnGJqfU702BZtXIr1SP2GvUIhM879QCyu7BMg2bkVHQr4i2ndI6ucDloAe37MhvHrQTZB4J6R2DDciroaRtcLqPVg5GxSBKhKxxgFYesUhfFgLGA5kVQQLGzxCFIh8VjV8z8+BbkKjRYxok9ssu5+bx9zP3GlQCBiKiepmttMcaOY7hviAiX8nf6y+WxMflhtZPRSR2xMLOX2QtCdy3WLnVghVvNRK08EU8ni8q/0GY2LO+Eri/zyX4WLDdoH8uyrhUnky3ovN9zNe7fV+r9oAwjlAbqIzUCtKDyMIoeabeQ8m/COOY1dOqTqsEiIEoSEMTGwVHcLNV4SleJ0eVqGlAs3rVUbxUG8oL65suhzRii+UM5iNNtmFkZ5kH8hrHThhV12oHBbPJqfrbxykhn0HsMK4ezP8vbxgtpjpSM3jF8p2hp3WTg1t3cTgocDw786IHUCGcEtHyS4zzRAGHoGLefFpKQ7dcGT2yJwObbwFjIUXToj3hFHbnT2dZlQUPZ1Tyw6PMkNb/Q5nMBnMyatEEdqBzQIYUNM2LVa1FBs6YPMa6/C51MVviZL8cI5yxbDEQyyCN+TyQcfJXc2kyRnd5cr36QY08lMZ3adWVWCvfryAzX8fD8tNLo60a5dA3lM2wuIxHDg1qGwq7O767lBdkbeRWdLcV1GsV9+7xRDg9A41ra2NR+NtSQvu61AndaBqr7DF73RlfEzXD2cZgp0tqbCkSCCEMVDzphYq0Z/wwcD/a06TVx5YbhL7DcwGvcoUBDJ+Muwcbrs4vcfKWKoNT/IfnLltrctZN6gcbpEQxQnvmVre1lptV8Q0s2YDSVUsP9803PDfbnodg+SW2jAJS5diNZCnTO3631sMQcwzeGLcW6l23gYQqMbkQvjOlkz+9Kw/f4Ltm5FfaqC0bBUbK8dqG2qr0UrtktFuEACDqPwJvwyAFfuJ4cTnLdwyedQFGyelC2GD7noj3b3g10+GdcK/xyzwwLUmxwjEP5qforqFwfnArcEZcrc4RQ/RcPmCsp9zCTLLY49bfxFbIUKTnFeI0LccnpXWQmOL7FlGQQ7w4Bg+KFZAFVMshPR7adsrKgE0GGLMjd2cTQ4Yt3lQnCWiG2Yo+t9YSaIlmJaWhG41zP5AVPJHtLx3Eqd1RV4jULQVihhWEc2u24Lc1ciuL1YA/htDewReu5Srpl7Y1XkkW3qPsDZetYNuQ5acip5vx07Pb7QFGTcbR4312C6GXCeSj99QjFP68OaklpYC+PwRZfmxec0PjBgb9rxX0k7wOwzgAj4lFfs6DVmD8WXuhyfJ+8SDO9t3CXKordYyztOoEK+bu/gn6IeM1RyOp2hiT9/HfYjzMNfRmH/JZyEEIAoaS7EYw==\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":1,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{},"partialJson":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{},"partialJson":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{},"partialJson":"{\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{},"partialJson":"{\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"command","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{},"partialJson":"{\"command"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{},"partialJson":"{\"command"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\":\"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":""},"partialJson":"{\"command\":\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":""},"partialJson":"{\"command\":\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"ls","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"1Xk2XWqR1ulgVF+AJkO7BUV5tbcFP1HuDrMrWoBVApM5IFGnqmsLcHNq51N9dBQxVXpshYmeu3qdsIl4P7G5ghwhWc3/LFTU1jQPKXsshquHEFL5sZdComr71OFNboxQj8KCDd7D7pOHyLXrAvbkB9uvkiLhNNDEKCaY2fVg/EIH0KoVCW0H4ARW+EeiUT/1JJxQZSBu3yTZaf6fYHCGwJ9vBRvcA+iTaU+uQByldbXAq6gp0Sx5khPwgbPPrY/+12fnjEOoaiL4CtL829A8ME3ffE9Y36yUZS95pR0lwAmtScxNbOZQAVkDvNK3wTDjA8E/sM3LkJzs+gM7SOkbDyJMxm9EGfIMXCgDd4ecmbo9690EeeHUR1aZO8DiJRLm3c6Q2n+U9zvLWLoWLpLJrVSGqvfPy1GFwvDbzkI6RFAPHDyEwn5kzss3JV8vyVpOAdNADVcff4PHnraAfMiLnzVbD82VgRHvr8IiAn9xdwW0OwwFs2mFZJqMoDjtsRjfiR+XdrRO/NQJsUNKA253IvZeTC9cou5htZbNHSB/VEKhu8DlZTDzYfzAHRyrg9wz/TaovEwAmVaiEQungMBPNoXVLAiQYptwF/ZFo87rpOOCu31nm5mtRuSnf6G/hXGsnMkvG47WheiNcqvGLYsKzi74tY/sx2u944zKL3diUsFPuA4RpIJUCO37XrtxLsErb/3AtzmNTkKRef3++iMPPeysq5SGbGAIBbKIak0R8dYS6bmZ6gRjM8Cm7eJ5VFrfeSmocmur3pG9zipACIDwVXMHh80OjRVL6fmgKfSJ9sv3ey+nnkmAyC1yXx00CFbrTLvWgIBwIHd00ArmSJF9vhdjCTRjj1bOml4WgDFAS6TFcNiB9+hdzNYnAoeSWg+RwVtg11oNLiAW/NXYRzUXUN1GMPrNnhpT1ut6if5w0gbsZbBgtJCJeM1ZTRwWz3caL3MPtNhJ/40cSYLcAzVjIkWl8fUnYyilfbKa7QQVcvAoFOH2Z6L6L4xaFc3miJOcidB0Aj2/Opal03hMmi87LKVy8Aas58fphWB9pBgyiLBB/WISf1CzX3Lzqtt4GqxLz0lSfpz434fcCn5O54Zwhvs8c9+7JTfB806NB726KvvkHie23j+0V8N+pR/NclxYpXXocA/UFZ43LWaSfb/31vH7c5IpxMrAQyEg7Gq2Fg3EaEZeRiAsFrgUFM6vwPlLAqeEFC1cYqlXzme/pwzo2XlIPJWFgL0R8w+sxctVd7c9OO7ETU2P7uhjjyfiCR8KKadzJodSE7Tu5ZcQ8glIuRR4GB7b/bHiuvtcCusoo/YUyvuHCuLRVHFfdP9hmkqSqXlnHVs/zF0z9FUAkh/8phGbl+Wm91CeyHYYedS2net2C4gBfTqcXhC23YIly8W8yJw8Mk+OJ/JGpk1h2R0GAaRn90rMKWf4sGEHvpzNS0QmE7QbdnN9npCCqq+HTzjzfxMGLKxXCaLg7bsijh4dsyM5XEVJPmEC/2RDTUzPGkDoaUtH9UJLlS0cGVgm2wGKvOPOn30mtdm6FY9Nr4Ppeb7Z+JYntP5uXhQ9II+e9U/BDyHeDiM8Ic00Yl6rrQo+yHmTyaPo0gNNn6+hUad6dHNskssXGYpFyc+qvlIm6AzgwnZWJQxUFwg4i763uv2lmVbheLLaKa2GGHmBngznXc7KxyOWOAQeipN640Wvzecx0Ta94YDYoSWpnDZwY71T9GA5d8PXEALESsDE5fp9Rzx8MnlTWjRx/+lj0AqxN6Jo89PtPBMu79i9zOag9CbVQ7E6kZv3xaJwT/L8WafMaY6wgSSCvDP+gKvAWSllDqGnAuqQJPYGfQookfh12u5izJMOsbi7fTQLIi0s+wiPIDHRlgIXjdjnwBk7mrk/j26veLHrqu0ZfGD4Hm6O/e4TX9LjAmzMMjoHMZ7UBIhimMVqMYxOaTWBs7dMUTy8dBYMOr8ijXd7/He2dY9Z8eoOEfL0zQw9QVIkXwvM8uSUUMj3YH9CjTM/cx4NC8ZopnoP7CIKJitQhu/4opvV6XeqbudQ46afPdW4Eob5hILE44oPoxuzT1R7XuySHHr5WffrnLe0RrQ9bCtrKctsM14cvlaYzyy+UhZ8lFX5vTnvHlTdhrieMvQE7qunpEl1Kl/OFDfj7Oy4c3sVSU2kbl6XUeBjjgw3cU4l7w4bZFNP0DjYw6cwTy1XDm+DSEb9CvZ25cyKqoRkJwKkZYzL+ieKTX9luO4CHZxCG2KxtlXHA3GJ4meDX5cMO/91xkAC250JL7R307u+/Ez+QjsnFkoj2fn/i/WEWe4KJ/BeMucUm/eFpOxDyYDv6J5ASyZJIV+pl6wFuAcKlDxnXUEuZ3/ukeScQ0s78vttJVI56QEBBtF6qmOdll5jg+zPoMrUL8uDprMfueY3BBDixFQhoHdcMNfwXxpNZ8SZlnnonv+vqRF/Kuogebvn9JL0yIdtP4vG5f5IpPwe8K1iX8iqkhRUefa5NwDtiyU1D95p53tH8ou/hXGw72548mHNBeLx74a22YWYYcTLDjK8yVrMNB2rt8OJFvozORrqvSVNJcvaphxs60LVEcE2NWkwYtRsNtKH88MoJJ5VpxOIxpjjn/qdcYvvbujIdqYdzE0yWXvzN4rRpsImnbwaC3o+88fcXd/x4VDf8REZm9WnkFrFPNh0G0osMGBUP72a2rPqYqygBKwZlazuwGn0o0EO9kl05Hu9MyfR06LW/4AuMMBbxf2wNFXYOMtyB82tOn8MKBOTTUaOoSRALjhVE+qwRvpXVGYfLasIu2KSoH2GLADdpVuMt7uPkSkNWbO3XdSVRS4Dmr40aGR+0d2YfoG/kYizxRFgh6owofE6pfTQt+bDGrPwISRfY90qfFb2ZVCq2nFNDXLjh0MrSc7eFK1e90roUc3VNlhF5FiwXxUFdCGYX2JpDPk1ycaOYX5mSqe9FG19kDZgG7i0Mw1cK9/HqM77z0/eZfNSjPaDKvgLCDsdkvhS/I2u35e64L9nzQgGW1Icv4cCx2G1AD4A1gCmpObNgWA24TqN4NIZH/L/vYrgnEMEPX96HtPlTna2j0Qmo7UIczFk4/DmhiOLHHLYLpV0CamruvlAba+/UWi8AV96YUHn+Q5CRh3KkTc7cUm0vmCXLtUJ26Ws1XS0GEbvig7bLGjFqk5x6JRYY7mMVb+Ypa98gFwiHAJjqcVDcqiiYd5JPtGeR8zozTBtTunfH35V/II3vtSqT5QFdkXaTjXkJxcnLPcLgCzLpjJTjifKdfhvMkSEist43oown+fotZ+DCKE5zAIkS54d1btr6fVIcunM8I7weM5O4Aa+Yy2sSsmKTJGT9vCYlWn+eErDDW/LYJ+bvfTqPYC5ZCywMK+Qa4QlhgZTeKN4hFk27pkaOAVRZuP9TYuw4cfHHzwUrw1e6FN7yRIOyMx+rjIdnXcQ+47Ot3WXBzAF+7KtdSzpu/I0vtTbmQV1Qv8ftvEI5Kqd3pGrXAFsFVxQEbdSJcOYu0zB8ZNnfbfUWVyFrLQ+zWuZlTGrHblDWa/m53i6q4wAr+55kYPz1u5Yc/kS4DSCIq4yHejsFk/DlZP6ls3Ov5KGzUbYlbIEhCsBJ+AsR9WrsHBvcEzqLudCnX/KQ313lZpqN+lQNGk4nWMpy3v1L+LZayfwVcHtRdm7QrGAxc+wz3hPfdRgOP5fBU31V2bXoJRgTEju/2dprkac7hj9hHS+7GYe8BFVq3ZKywUYhYb0s66yF0a1TtW6cfJMOFuBvgNsU4Q4s3QlyD/JsvnhCBKHspoGJ64qebmeh13CCYzcQNnSb6LrUDH7gXc3abAi1iQ1s3gwnpvzcV+aObtIpY5lNsCSQ++gLJPkXukytj8/DgKWrwD0kuC270p5Ze7dZUotQSGXueoGyV85Pdu6OqBuVEYRu8xkfgnJ8iu5OpnsJb097lp7+G0EYLryxwWDlJZI8AfT/ySE+lQeSmw5OKD1Hk6goBZu5EGX6czZ7GLD94q8jMaV7aNe8XX7VLOWbLgUeV3hq7mPAmn7Sd1+ACaaUsyDezSnLOLbDjK9/xyFHObP51Yx1u0P3fDpaItF2iRkivBgyGdtzQ8h+2tHIFaa2czJ0RiW10hwskih2XEGDpZGWUScy000p8Cw7+tS5/OAwn2e5w33SP3+AEN0A8l4bC1wts/s36pMY+FifsXVryqU8CBJWvmFMtzBF2nEOkjx6JmhkuxOeuJkO+TSkZu2PLLSGgcg9qBCrYqqn03+0woBeOHH7EsF4LpMAddrsPdq+8J0p6e+ALsuZoohck7hH33t5H4ORp0AZPlMlguJZ5vkqwdWUXAnZTXloZWVLfBVdv1omNV/lZjA9+MOK576HOo/gBhYDzZgnl4JaIfeEXDnAA9uSZuoddoFcns/UhasTqwgeCKcckVWsB9ba0d/cCT49uazLQ+aSumLsxy/oTJz9QosQMtWnGJqfU702BZtXIr1SP2GvUIhM879QCyu7BMg2bkVHQr4i2ndI6ucDloAe37MhvHrQTZB4J6R2DDciroaRtcLqPVg5GxSBKhKxxgFYesUhfFgLGA5kVQQLGzxCFIh8VjV8z8+BbkKjRYxok9ssu5+bx9zP3GlQCBiKiepmttMcaOY7hviAiX8nf6y+WxMflhtZPRSR2xMLOX2QtCdy3WLnVghVvNRK08EU8ni8q/0GY2LO+Eri/zyX4WLDdoH8uyrhUnky3ovN9zNe7fV+r9oAwjlAbqIzUCtKDyMIoeabeQ8m/COOY1dOqTqsEiIEoSEMTGwVHcLNV4SleJ0eVqGlAs3rVUbxUG8oL65suhzRii+UM5iNNtmFkZ5kH8hrHThhV12oHBbPJqfrbxykhn0HsMK4ezP8vbxgtpjpSM3jF8p2hp3WTg1t3cTgocDw786IHUCGcEtHyS4zzRAGHoGLefFpKQ7dcGT2yJwObbwFjIUXToj3hFHbnT2dZlQUPZ1Tyw6PMkNb/Q5nMBnMyatEEdqBzQIYUNM2LVa1FBs6YPMa6/C51MVviZL8cI5yxbDEQyyCN+TyQcfJXc2kyRnd5cr36QY08lMZ3adWVWCvfryAzX8fD8tNLo60a5dA3lM2wuIxHDg1qGwq7O767lBdkbeRWdLcV1GsV9+7xRDg9A41ra2NR+NtSQvu61AndaBqr7DF73RlfEzXD2cZgp0tqbCkSCCEMVDzphYq0Z/wwcD/a06TVx5YbhL7DcwGvcoUBDJ+Muwcbrs4vcfKWKoNT/IfnLltrctZN6gcbpEQxQnvmVre1lptV8Q0s2YDSVUsP9803PDfbnodg+SW2jAJS5diNZCnTO3631sMQcwzeGLcW6l23gYQqMbkQvjOlkz+9Kw/f4Ltm5FfaqC0bBUbK8dqG2qr0UrtktFuEACDqPwJvwyAFfuJ4cTnLdwyedQFGyelC2GD7noj3b3g10+GdcK/xyzwwLUmxwjEP5qforqFwfnArcEZcrc4RQ/RcPmCsp9zCTLLY49bfxFbIUKTnFeI0LccnpXWQmOL7FlGQQ7w4Bg+KFZAFVMshPR7adsrKgE0GGLMjd2cTQ4Yt3lQnCWiG2Yo+t9YSaIlmJaWhG41zP5AVPJHtLx3Eqd1RV4jULQVihhWEc2u24Lc1ciuL1YA/htDewReu5Srpl7Y1XkkW3qPsDZetYNuQ5acip5vx07Pb7QFGTcbR4312C6GXCeSj99QjFP68OaklpYC+PwRZfmxec0PjBgb9rxX0k7wOwzgAj4lFfs6DVmD8WXuhyfJ+8SDO9t3CXKordYyztOoEK+bu/gn6IeM1RyOp2hiT9/HfYjzMNfRmH/JZyEEIAoaS7EYw==\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls"},"partialJson":"{\"command\":\"ls"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"1Xk2XWqR1ulgVF+AJkO7BUV5tbcFP1HuDrMrWoBVApM5IFGnqmsLcHNq51N9dBQxVXpshYmeu3qdsIl4P7G5ghwhWc3/LFTU1jQPKXsshquHEFL5sZdComr71OFNboxQj8KCDd7D7pOHyLXrAvbkB9uvkiLhNNDEKCaY2fVg/EIH0KoVCW0H4ARW+EeiUT/1JJxQZSBu3yTZaf6fYHCGwJ9vBRvcA+iTaU+uQByldbXAq6gp0Sx5khPwgbPPrY/+12fnjEOoaiL4CtL829A8ME3ffE9Y36yUZS95pR0lwAmtScxNbOZQAVkDvNK3wTDjA8E/sM3LkJzs+gM7SOkbDyJMxm9EGfIMXCgDd4ecmbo9690EeeHUR1aZO8DiJRLm3c6Q2n+U9zvLWLoWLpLJrVSGqvfPy1GFwvDbzkI6RFAPHDyEwn5kzss3JV8vyVpOAdNADVcff4PHnraAfMiLnzVbD82VgRHvr8IiAn9xdwW0OwwFs2mFZJqMoDjtsRjfiR+XdrRO/NQJsUNKA253IvZeTC9cou5htZbNHSB/VEKhu8DlZTDzYfzAHRyrg9wz/TaovEwAmVaiEQungMBPNoXVLAiQYptwF/ZFo87rpOOCu31nm5mtRuSnf6G/hXGsnMkvG47WheiNcqvGLYsKzi74tY/sx2u944zKL3diUsFPuA4RpIJUCO37XrtxLsErb/3AtzmNTkKRef3++iMPPeysq5SGbGAIBbKIak0R8dYS6bmZ6gRjM8Cm7eJ5VFrfeSmocmur3pG9zipACIDwVXMHh80OjRVL6fmgKfSJ9sv3ey+nnkmAyC1yXx00CFbrTLvWgIBwIHd00ArmSJF9vhdjCTRjj1bOml4WgDFAS6TFcNiB9+hdzNYnAoeSWg+RwVtg11oNLiAW/NXYRzUXUN1GMPrNnhpT1ut6if5w0gbsZbBgtJCJeM1ZTRwWz3caL3MPtNhJ/40cSYLcAzVjIkWl8fUnYyilfbKa7QQVcvAoFOH2Z6L6L4xaFc3miJOcidB0Aj2/Opal03hMmi87LKVy8Aas58fphWB9pBgyiLBB/WISf1CzX3Lzqtt4GqxLz0lSfpz434fcCn5O54Zwhvs8c9+7JTfB806NB726KvvkHie23j+0V8N+pR/NclxYpXXocA/UFZ43LWaSfb/31vH7c5IpxMrAQyEg7Gq2Fg3EaEZeRiAsFrgUFM6vwPlLAqeEFC1cYqlXzme/pwzo2XlIPJWFgL0R8w+sxctVd7c9OO7ETU2P7uhjjyfiCR8KKadzJodSE7Tu5ZcQ8glIuRR4GB7b/bHiuvtcCusoo/YUyvuHCuLRVHFfdP9hmkqSqXlnHVs/zF0z9FUAkh/8phGbl+Wm91CeyHYYedS2net2C4gBfTqcXhC23YIly8W8yJw8Mk+OJ/JGpk1h2R0GAaRn90rMKWf4sGEHvpzNS0QmE7QbdnN9npCCqq+HTzjzfxMGLKxXCaLg7bsijh4dsyM5XEVJPmEC/2RDTUzPGkDoaUtH9UJLlS0cGVgm2wGKvOPOn30mtdm6FY9Nr4Ppeb7Z+JYntP5uXhQ9II+e9U/BDyHeDiM8Ic00Yl6rrQo+yHmTyaPo0gNNn6+hUad6dHNskssXGYpFyc+qvlIm6AzgwnZWJQxUFwg4i763uv2lmVbheLLaKa2GGHmBngznXc7KxyOWOAQeipN640Wvzecx0Ta94YDYoSWpnDZwY71T9GA5d8PXEALESsDE5fp9Rzx8MnlTWjRx/+lj0AqxN6Jo89PtPBMu79i9zOag9CbVQ7E6kZv3xaJwT/L8WafMaY6wgSSCvDP+gKvAWSllDqGnAuqQJPYGfQookfh12u5izJMOsbi7fTQLIi0s+wiPIDHRlgIXjdjnwBk7mrk/j26veLHrqu0ZfGD4Hm6O/e4TX9LjAmzMMjoHMZ7UBIhimMVqMYxOaTWBs7dMUTy8dBYMOr8ijXd7/He2dY9Z8eoOEfL0zQw9QVIkXwvM8uSUUMj3YH9CjTM/cx4NC8ZopnoP7CIKJitQhu/4opvV6XeqbudQ46afPdW4Eob5hILE44oPoxuzT1R7XuySHHr5WffrnLe0RrQ9bCtrKctsM14cvlaYzyy+UhZ8lFX5vTnvHlTdhrieMvQE7qunpEl1Kl/OFDfj7Oy4c3sVSU2kbl6XUeBjjgw3cU4l7w4bZFNP0DjYw6cwTy1XDm+DSEb9CvZ25cyKqoRkJwKkZYzL+ieKTX9luO4CHZxCG2KxtlXHA3GJ4meDX5cMO/91xkAC250JL7R307u+/Ez+QjsnFkoj2fn/i/WEWe4KJ/BeMucUm/eFpOxDyYDv6J5ASyZJIV+pl6wFuAcKlDxnXUEuZ3/ukeScQ0s78vttJVI56QEBBtF6qmOdll5jg+zPoMrUL8uDprMfueY3BBDixFQhoHdcMNfwXxpNZ8SZlnnonv+vqRF/Kuogebvn9JL0yIdtP4vG5f5IpPwe8K1iX8iqkhRUefa5NwDtiyU1D95p53tH8ou/hXGw72548mHNBeLx74a22YWYYcTLDjK8yVrMNB2rt8OJFvozORrqvSVNJcvaphxs60LVEcE2NWkwYtRsNtKH88MoJJ5VpxOIxpjjn/qdcYvvbujIdqYdzE0yWXvzN4rRpsImnbwaC3o+88fcXd/x4VDf8REZm9WnkFrFPNh0G0osMGBUP72a2rPqYqygBKwZlazuwGn0o0EO9kl05Hu9MyfR06LW/4AuMMBbxf2wNFXYOMtyB82tOn8MKBOTTUaOoSRALjhVE+qwRvpXVGYfLasIu2KSoH2GLADdpVuMt7uPkSkNWbO3XdSVRS4Dmr40aGR+0d2YfoG/kYizxRFgh6owofE6pfTQt+bDGrPwISRfY90qfFb2ZVCq2nFNDXLjh0MrSc7eFK1e90roUc3VNlhF5FiwXxUFdCGYX2JpDPk1ycaOYX5mSqe9FG19kDZgG7i0Mw1cK9/HqM77z0/eZfNSjPaDKvgLCDsdkvhS/I2u35e64L9nzQgGW1Icv4cCx2G1AD4A1gCmpObNgWA24TqN4NIZH/L/vYrgnEMEPX96HtPlTna2j0Qmo7UIczFk4/DmhiOLHHLYLpV0CamruvlAba+/UWi8AV96YUHn+Q5CRh3KkTc7cUm0vmCXLtUJ26Ws1XS0GEbvig7bLGjFqk5x6JRYY7mMVb+Ypa98gFwiHAJjqcVDcqiiYd5JPtGeR8zozTBtTunfH35V/II3vtSqT5QFdkXaTjXkJxcnLPcLgCzLpjJTjifKdfhvMkSEist43oown+fotZ+DCKE5zAIkS54d1btr6fVIcunM8I7weM5O4Aa+Yy2sSsmKTJGT9vCYlWn+eErDDW/LYJ+bvfTqPYC5ZCywMK+Qa4QlhgZTeKN4hFk27pkaOAVRZuP9TYuw4cfHHzwUrw1e6FN7yRIOyMx+rjIdnXcQ+47Ot3WXBzAF+7KtdSzpu/I0vtTbmQV1Qv8ftvEI5Kqd3pGrXAFsFVxQEbdSJcOYu0zB8ZNnfbfUWVyFrLQ+zWuZlTGrHblDWa/m53i6q4wAr+55kYPz1u5Yc/kS4DSCIq4yHejsFk/DlZP6ls3Ov5KGzUbYlbIEhCsBJ+AsR9WrsHBvcEzqLudCnX/KQ313lZpqN+lQNGk4nWMpy3v1L+LZayfwVcHtRdm7QrGAxc+wz3hPfdRgOP5fBU31V2bXoJRgTEju/2dprkac7hj9hHS+7GYe8BFVq3ZKywUYhYb0s66yF0a1TtW6cfJMOFuBvgNsU4Q4s3QlyD/JsvnhCBKHspoGJ64qebmeh13CCYzcQNnSb6LrUDH7gXc3abAi1iQ1s3gwnpvzcV+aObtIpY5lNsCSQ++gLJPkXukytj8/DgKWrwD0kuC270p5Ze7dZUotQSGXueoGyV85Pdu6OqBuVEYRu8xkfgnJ8iu5OpnsJb097lp7+G0EYLryxwWDlJZI8AfT/ySE+lQeSmw5OKD1Hk6goBZu5EGX6czZ7GLD94q8jMaV7aNe8XX7VLOWbLgUeV3hq7mPAmn7Sd1+ACaaUsyDezSnLOLbDjK9/xyFHObP51Yx1u0P3fDpaItF2iRkivBgyGdtzQ8h+2tHIFaa2czJ0RiW10hwskih2XEGDpZGWUScy000p8Cw7+tS5/OAwn2e5w33SP3+AEN0A8l4bC1wts/s36pMY+FifsXVryqU8CBJWvmFMtzBF2nEOkjx6JmhkuxOeuJkO+TSkZu2PLLSGgcg9qBCrYqqn03+0woBeOHH7EsF4LpMAddrsPdq+8J0p6e+ALsuZoohck7hH33t5H4ORp0AZPlMlguJZ5vkqwdWUXAnZTXloZWVLfBVdv1omNV/lZjA9+MOK576HOo/gBhYDzZgnl4JaIfeEXDnAA9uSZuoddoFcns/UhasTqwgeCKcckVWsB9ba0d/cCT49uazLQ+aSumLsxy/oTJz9QosQMtWnGJqfU702BZtXIr1SP2GvUIhM879QCyu7BMg2bkVHQr4i2ndI6ucDloAe37MhvHrQTZB4J6R2DDciroaRtcLqPVg5GxSBKhKxxgFYesUhfFgLGA5kVQQLGzxCFIh8VjV8z8+BbkKjRYxok9ssu5+bx9zP3GlQCBiKiepmttMcaOY7hviAiX8nf6y+WxMflhtZPRSR2xMLOX2QtCdy3WLnVghVvNRK08EU8ni8q/0GY2LO+Eri/zyX4WLDdoH8uyrhUnky3ovN9zNe7fV+r9oAwjlAbqIzUCtKDyMIoeabeQ8m/COOY1dOqTqsEiIEoSEMTGwVHcLNV4SleJ0eVqGlAs3rVUbxUG8oL65suhzRii+UM5iNNtmFkZ5kH8hrHThhV12oHBbPJqfrbxykhn0HsMK4ezP8vbxgtpjpSM3jF8p2hp3WTg1t3cTgocDw786IHUCGcEtHyS4zzRAGHoGLefFpKQ7dcGT2yJwObbwFjIUXToj3hFHbnT2dZlQUPZ1Tyw6PMkNb/Q5nMBnMyatEEdqBzQIYUNM2LVa1FBs6YPMa6/C51MVviZL8cI5yxbDEQyyCN+TyQcfJXc2kyRnd5cr36QY08lMZ3adWVWCvfryAzX8fD8tNLo60a5dA3lM2wuIxHDg1qGwq7O767lBdkbeRWdLcV1GsV9+7xRDg9A41ra2NR+NtSQvu61AndaBqr7DF73RlfEzXD2cZgp0tqbCkSCCEMVDzphYq0Z/wwcD/a06TVx5YbhL7DcwGvcoUBDJ+Muwcbrs4vcfKWKoNT/IfnLltrctZN6gcbpEQxQnvmVre1lptV8Q0s2YDSVUsP9803PDfbnodg+SW2jAJS5diNZCnTO3631sMQcwzeGLcW6l23gYQqMbkQvjOlkz+9Kw/f4Ltm5FfaqC0bBUbK8dqG2qr0UrtktFuEACDqPwJvwyAFfuJ4cTnLdwyedQFGyelC2GD7noj3b3g10+GdcK/xyzwwLUmxwjEP5qforqFwfnArcEZcrc4RQ/RcPmCsp9zCTLLY49bfxFbIUKTnFeI0LccnpXWQmOL7FlGQQ7w4Bg+KFZAFVMshPR7adsrKgE0GGLMjd2cTQ4Yt3lQnCWiG2Yo+t9YSaIlmJaWhG41zP5AVPJHtLx3Eqd1RV4jULQVihhWEc2u24Lc1ciuL1YA/htDewReu5Srpl7Y1XkkW3qPsDZetYNuQ5acip5vx07Pb7QFGTcbR4312C6GXCeSj99QjFP68OaklpYC+PwRZfmxec0PjBgb9rxX0k7wOwzgAj4lFfs6DVmD8WXuhyfJ+8SDO9t3CXKordYyztOoEK+bu/gn6IeM1RyOp2hiT9/HfYjzMNfRmH/JZyEEIAoaS7EYw==\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls"},"partialJson":"{\"command\":\"ls"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":" -","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"1Xk2XWqR1ulgVF+AJkO7BUV5tbcFP1HuDrMrWoBVApM5IFGnqmsLcHNq51N9dBQxVXpshYmeu3qdsIl4P7G5ghwhWc3/LFTU1jQPKXsshquHEFL5sZdComr71OFNboxQj8KCDd7D7pOHyLXrAvbkB9uvkiLhNNDEKCaY2fVg/EIH0KoVCW0H4ARW+EeiUT/1JJxQZSBu3yTZaf6fYHCGwJ9vBRvcA+iTaU+uQByldbXAq6gp0Sx5khPwgbPPrY/+12fnjEOoaiL4CtL829A8ME3ffE9Y36yUZS95pR0lwAmtScxNbOZQAVkDvNK3wTDjA8E/sM3LkJzs+gM7SOkbDyJMxm9EGfIMXCgDd4ecmbo9690EeeHUR1aZO8DiJRLm3c6Q2n+U9zvLWLoWLpLJrVSGqvfPy1GFwvDbzkI6RFAPHDyEwn5kzss3JV8vyVpOAdNADVcff4PHnraAfMiLnzVbD82VgRHvr8IiAn9xdwW0OwwFs2mFZJqMoDjtsRjfiR+XdrRO/NQJsUNKA253IvZeTC9cou5htZbNHSB/VEKhu8DlZTDzYfzAHRyrg9wz/TaovEwAmVaiEQungMBPNoXVLAiQYptwF/ZFo87rpOOCu31nm5mtRuSnf6G/hXGsnMkvG47WheiNcqvGLYsKzi74tY/sx2u944zKL3diUsFPuA4RpIJUCO37XrtxLsErb/3AtzmNTkKRef3++iMPPeysq5SGbGAIBbKIak0R8dYS6bmZ6gRjM8Cm7eJ5VFrfeSmocmur3pG9zipACIDwVXMHh80OjRVL6fmgKfSJ9sv3ey+nnkmAyC1yXx00CFbrTLvWgIBwIHd00ArmSJF9vhdjCTRjj1bOml4WgDFAS6TFcNiB9+hdzNYnAoeSWg+RwVtg11oNLiAW/NXYRzUXUN1GMPrNnhpT1ut6if5w0gbsZbBgtJCJeM1ZTRwWz3caL3MPtNhJ/40cSYLcAzVjIkWl8fUnYyilfbKa7QQVcvAoFOH2Z6L6L4xaFc3miJOcidB0Aj2/Opal03hMmi87LKVy8Aas58fphWB9pBgyiLBB/WISf1CzX3Lzqtt4GqxLz0lSfpz434fcCn5O54Zwhvs8c9+7JTfB806NB726KvvkHie23j+0V8N+pR/NclxYpXXocA/UFZ43LWaSfb/31vH7c5IpxMrAQyEg7Gq2Fg3EaEZeRiAsFrgUFM6vwPlLAqeEFC1cYqlXzme/pwzo2XlIPJWFgL0R8w+sxctVd7c9OO7ETU2P7uhjjyfiCR8KKadzJodSE7Tu5ZcQ8glIuRR4GB7b/bHiuvtcCusoo/YUyvuHCuLRVHFfdP9hmkqSqXlnHVs/zF0z9FUAkh/8phGbl+Wm91CeyHYYedS2net2C4gBfTqcXhC23YIly8W8yJw8Mk+OJ/JGpk1h2R0GAaRn90rMKWf4sGEHvpzNS0QmE7QbdnN9npCCqq+HTzjzfxMGLKxXCaLg7bsijh4dsyM5XEVJPmEC/2RDTUzPGkDoaUtH9UJLlS0cGVgm2wGKvOPOn30mtdm6FY9Nr4Ppeb7Z+JYntP5uXhQ9II+e9U/BDyHeDiM8Ic00Yl6rrQo+yHmTyaPo0gNNn6+hUad6dHNskssXGYpFyc+qvlIm6AzgwnZWJQxUFwg4i763uv2lmVbheLLaKa2GGHmBngznXc7KxyOWOAQeipN640Wvzecx0Ta94YDYoSWpnDZwY71T9GA5d8PXEALESsDE5fp9Rzx8MnlTWjRx/+lj0AqxN6Jo89PtPBMu79i9zOag9CbVQ7E6kZv3xaJwT/L8WafMaY6wgSSCvDP+gKvAWSllDqGnAuqQJPYGfQookfh12u5izJMOsbi7fTQLIi0s+wiPIDHRlgIXjdjnwBk7mrk/j26veLHrqu0ZfGD4Hm6O/e4TX9LjAmzMMjoHMZ7UBIhimMVqMYxOaTWBs7dMUTy8dBYMOr8ijXd7/He2dY9Z8eoOEfL0zQw9QVIkXwvM8uSUUMj3YH9CjTM/cx4NC8ZopnoP7CIKJitQhu/4opvV6XeqbudQ46afPdW4Eob5hILE44oPoxuzT1R7XuySHHr5WffrnLe0RrQ9bCtrKctsM14cvlaYzyy+UhZ8lFX5vTnvHlTdhrieMvQE7qunpEl1Kl/OFDfj7Oy4c3sVSU2kbl6XUeBjjgw3cU4l7w4bZFNP0DjYw6cwTy1XDm+DSEb9CvZ25cyKqoRkJwKkZYzL+ieKTX9luO4CHZxCG2KxtlXHA3GJ4meDX5cMO/91xkAC250JL7R307u+/Ez+QjsnFkoj2fn/i/WEWe4KJ/BeMucUm/eFpOxDyYDv6J5ASyZJIV+pl6wFuAcKlDxnXUEuZ3/ukeScQ0s78vttJVI56QEBBtF6qmOdll5jg+zPoMrUL8uDprMfueY3BBDixFQhoHdcMNfwXxpNZ8SZlnnonv+vqRF/Kuogebvn9JL0yIdtP4vG5f5IpPwe8K1iX8iqkhRUefa5NwDtiyU1D95p53tH8ou/hXGw72548mHNBeLx74a22YWYYcTLDjK8yVrMNB2rt8OJFvozORrqvSVNJcvaphxs60LVEcE2NWkwYtRsNtKH88MoJJ5VpxOIxpjjn/qdcYvvbujIdqYdzE0yWXvzN4rRpsImnbwaC3o+88fcXd/x4VDf8REZm9WnkFrFPNh0G0osMGBUP72a2rPqYqygBKwZlazuwGn0o0EO9kl05Hu9MyfR06LW/4AuMMBbxf2wNFXYOMtyB82tOn8MKBOTTUaOoSRALjhVE+qwRvpXVGYfLasIu2KSoH2GLADdpVuMt7uPkSkNWbO3XdSVRS4Dmr40aGR+0d2YfoG/kYizxRFgh6owofE6pfTQt+bDGrPwISRfY90qfFb2ZVCq2nFNDXLjh0MrSc7eFK1e90roUc3VNlhF5FiwXxUFdCGYX2JpDPk1ycaOYX5mSqe9FG19kDZgG7i0Mw1cK9/HqM77z0/eZfNSjPaDKvgLCDsdkvhS/I2u35e64L9nzQgGW1Icv4cCx2G1AD4A1gCmpObNgWA24TqN4NIZH/L/vYrgnEMEPX96HtPlTna2j0Qmo7UIczFk4/DmhiOLHHLYLpV0CamruvlAba+/UWi8AV96YUHn+Q5CRh3KkTc7cUm0vmCXLtUJ26Ws1XS0GEbvig7bLGjFqk5x6JRYY7mMVb+Ypa98gFwiHAJjqcVDcqiiYd5JPtGeR8zozTBtTunfH35V/II3vtSqT5QFdkXaTjXkJxcnLPcLgCzLpjJTjifKdfhvMkSEist43oown+fotZ+DCKE5zAIkS54d1btr6fVIcunM8I7weM5O4Aa+Yy2sSsmKTJGT9vCYlWn+eErDDW/LYJ+bvfTqPYC5ZCywMK+Qa4QlhgZTeKN4hFk27pkaOAVRZuP9TYuw4cfHHzwUrw1e6FN7yRIOyMx+rjIdnXcQ+47Ot3WXBzAF+7KtdSzpu/I0vtTbmQV1Qv8ftvEI5Kqd3pGrXAFsFVxQEbdSJcOYu0zB8ZNnfbfUWVyFrLQ+zWuZlTGrHblDWa/m53i6q4wAr+55kYPz1u5Yc/kS4DSCIq4yHejsFk/DlZP6ls3Ov5KGzUbYlbIEhCsBJ+AsR9WrsHBvcEzqLudCnX/KQ313lZpqN+lQNGk4nWMpy3v1L+LZayfwVcHtRdm7QrGAxc+wz3hPfdRgOP5fBU31V2bXoJRgTEju/2dprkac7hj9hHS+7GYe8BFVq3ZKywUYhYb0s66yF0a1TtW6cfJMOFuBvgNsU4Q4s3QlyD/JsvnhCBKHspoGJ64qebmeh13CCYzcQNnSb6LrUDH7gXc3abAi1iQ1s3gwnpvzcV+aObtIpY5lNsCSQ++gLJPkXukytj8/DgKWrwD0kuC270p5Ze7dZUotQSGXueoGyV85Pdu6OqBuVEYRu8xkfgnJ8iu5OpnsJb097lp7+G0EYLryxwWDlJZI8AfT/ySE+lQeSmw5OKD1Hk6goBZu5EGX6czZ7GLD94q8jMaV7aNe8XX7VLOWbLgUeV3hq7mPAmn7Sd1+ACaaUsyDezSnLOLbDjK9/xyFHObP51Yx1u0P3fDpaItF2iRkivBgyGdtzQ8h+2tHIFaa2czJ0RiW10hwskih2XEGDpZGWUScy000p8Cw7+tS5/OAwn2e5w33SP3+AEN0A8l4bC1wts/s36pMY+FifsXVryqU8CBJWvmFMtzBF2nEOkjx6JmhkuxOeuJkO+TSkZu2PLLSGgcg9qBCrYqqn03+0woBeOHH7EsF4LpMAddrsPdq+8J0p6e+ALsuZoohck7hH33t5H4ORp0AZPlMlguJZ5vkqwdWUXAnZTXloZWVLfBVdv1omNV/lZjA9+MOK576HOo/gBhYDzZgnl4JaIfeEXDnAA9uSZuoddoFcns/UhasTqwgeCKcckVWsB9ba0d/cCT49uazLQ+aSumLsxy/oTJz9QosQMtWnGJqfU702BZtXIr1SP2GvUIhM879QCyu7BMg2bkVHQr4i2ndI6ucDloAe37MhvHrQTZB4J6R2DDciroaRtcLqPVg5GxSBKhKxxgFYesUhfFgLGA5kVQQLGzxCFIh8VjV8z8+BbkKjRYxok9ssu5+bx9zP3GlQCBiKiepmttMcaOY7hviAiX8nf6y+WxMflhtZPRSR2xMLOX2QtCdy3WLnVghVvNRK08EU8ni8q/0GY2LO+Eri/zyX4WLDdoH8uyrhUnky3ovN9zNe7fV+r9oAwjlAbqIzUCtKDyMIoeabeQ8m/COOY1dOqTqsEiIEoSEMTGwVHcLNV4SleJ0eVqGlAs3rVUbxUG8oL65suhzRii+UM5iNNtmFkZ5kH8hrHThhV12oHBbPJqfrbxykhn0HsMK4ezP8vbxgtpjpSM3jF8p2hp3WTg1t3cTgocDw786IHUCGcEtHyS4zzRAGHoGLefFpKQ7dcGT2yJwObbwFjIUXToj3hFHbnT2dZlQUPZ1Tyw6PMkNb/Q5nMBnMyatEEdqBzQIYUNM2LVa1FBs6YPMa6/C51MVviZL8cI5yxbDEQyyCN+TyQcfJXc2kyRnd5cr36QY08lMZ3adWVWCvfryAzX8fD8tNLo60a5dA3lM2wuIxHDg1qGwq7O767lBdkbeRWdLcV1GsV9+7xRDg9A41ra2NR+NtSQvu61AndaBqr7DF73RlfEzXD2cZgp0tqbCkSCCEMVDzphYq0Z/wwcD/a06TVx5YbhL7DcwGvcoUBDJ+Muwcbrs4vcfKWKoNT/IfnLltrctZN6gcbpEQxQnvmVre1lptV8Q0s2YDSVUsP9803PDfbnodg+SW2jAJS5diNZCnTO3631sMQcwzeGLcW6l23gYQqMbkQvjOlkz+9Kw/f4Ltm5FfaqC0bBUbK8dqG2qr0UrtktFuEACDqPwJvwyAFfuJ4cTnLdwyedQFGyelC2GD7noj3b3g10+GdcK/xyzwwLUmxwjEP5qforqFwfnArcEZcrc4RQ/RcPmCsp9zCTLLY49bfxFbIUKTnFeI0LccnpXWQmOL7FlGQQ7w4Bg+KFZAFVMshPR7adsrKgE0GGLMjd2cTQ4Yt3lQnCWiG2Yo+t9YSaIlmJaWhG41zP5AVPJHtLx3Eqd1RV4jULQVihhWEc2u24Lc1ciuL1YA/htDewReu5Srpl7Y1XkkW3qPsDZetYNuQ5acip5vx07Pb7QFGTcbR4312C6GXCeSj99QjFP68OaklpYC+PwRZfmxec0PjBgb9rxX0k7wOwzgAj4lFfs6DVmD8WXuhyfJ+8SDO9t3CXKordYyztOoEK+bu/gn6IeM1RyOp2hiT9/HfYjzMNfRmH/JZyEEIAoaS7EYw==\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -"},"partialJson":"{\"command\":\"ls -"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -"},"partialJson":"{\"command\":\"ls -"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"la","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":1,"toolCall":{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|sTnF4LeGgpctoojYb6PlQRAVG9stPHMEoH9SsCjCj2JDvhdWNSRofoe5AT6Vw1DDveDGMKcPOUFPoGj3IQP6eX4VH0nPJ1hKY2DizlDycTIC49dljgCFBv3p6C+CQ21evDtnh5bvAwmnfJG8HsQGNPWKPly7UC/jgHoIpiVjRymfEdATE8qCagrRzFCkyc+yOKrNd/3EP4uXRtnKXk1V4m3Xyvza9x8lNNEK/L8DfhVIh9P90NsW7YCyUArQWOQf0AZfskColwcwySP1wiPvJQzAzUJYNF26x8yXK2QVlm5DzZ94EOLWtf54julCs/r1uWYsM/rQPAKrbKC4Y2VO1Ruuui9w1JtFPPKbd8fDuFQLXTMKj7ACCkTs+qCL+glp/aBBgFrpqPr/mk3pOYDG/Lcnp7imR8U=","name":"bash","arguments":{"command":"ls -la"}},"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941589217,"responseId":"h+3A3E1OgKJEfqss5bQoOU/jouQDzV1baSAOfMf7YWwOLxW9VIW4CarIe/d2wrw9v3kL68TrfOckgu+NQ/25DMbNBTnQNR/8fT6DHcHKuBfSR/woJiHgedrZsra501QwGY7JlERF2z8G8B2xooOyBRW8pafaVVIZy0UEZXQ/igfBSYuDmLSx2G0QceHXkCwzXM8AksNzhhuiOfyV4i3knO2n7TJxsYs34zt27zQXf9t1mtTWp+HhVbwUxn+IVAPYTMhARymuThaQuPYWMT2NeOUka1z8Osfr0Pew6tU2V5XBXeZVup7hcdkxOhw4Xx9z2j6GUEG0FYJ6ZcombKSxLYnhA2dRmtZ7Qny9zWtXdoYYpAYRXKuuBK+9zPLxyHbdscdSNGg40YVvXTUlgplXInFJG1aCKSVOzg=="}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"1Xk2XWqR1ulgVF+AJkO7BUV5tbcFP1HuDrMrWoBVApM5IFGnqmsLcHNq51N9dBQxVXpshYmeu3qdsIl4P7G5ghwhWc3/LFTU1jQPKXsshquHEFL5sZdComr71OFNboxQj8KCDd7D7pOHyLXrAvbkB9uvkiLhNNDEKCaY2fVg/EIH0KoVCW0H4ARW+EeiUT/1JJxQZSBu3yTZaf6fYHCGwJ9vBRvcA+iTaU+uQByldbXAq6gp0Sx5khPwgbPPrY/+12fnjEOoaiL4CtL829A8ME3ffE9Y36yUZS95pR0lwAmtScxNbOZQAVkDvNK3wTDjA8E/sM3LkJzs+gM7SOkbDyJMxm9EGfIMXCgDd4ecmbo9690EeeHUR1aZO8DiJRLm3c6Q2n+U9zvLWLoWLpLJrVSGqvfPy1GFwvDbzkI6RFAPHDyEwn5kzss3JV8vyVpOAdNADVcff4PHnraAfMiLnzVbD82VgRHvr8IiAn9xdwW0OwwFs2mFZJqMoDjtsRjfiR+XdrRO/NQJsUNKA253IvZeTC9cou5htZbNHSB/VEKhu8DlZTDzYfzAHRyrg9wz/TaovEwAmVaiEQungMBPNoXVLAiQYptwF/ZFo87rpOOCu31nm5mtRuSnf6G/hXGsnMkvG47WheiNcqvGLYsKzi74tY/sx2u944zKL3diUsFPuA4RpIJUCO37XrtxLsErb/3AtzmNTkKRef3++iMPPeysq5SGbGAIBbKIak0R8dYS6bmZ6gRjM8Cm7eJ5VFrfeSmocmur3pG9zipACIDwVXMHh80OjRVL6fmgKfSJ9sv3ey+nnkmAyC1yXx00CFbrTLvWgIBwIHd00ArmSJF9vhdjCTRjj1bOml4WgDFAS6TFcNiB9+hdzNYnAoeSWg+RwVtg11oNLiAW/NXYRzUXUN1GMPrNnhpT1ut6if5w0gbsZbBgtJCJeM1ZTRwWz3caL3MPtNhJ/40cSYLcAzVjIkWl8fUnYyilfbKa7QQVcvAoFOH2Z6L6L4xaFc3miJOcidB0Aj2/Opal03hMmi87LKVy8Aas58fphWB9pBgyiLBB/WISf1CzX3Lzqtt4GqxLz0lSfpz434fcCn5O54Zwhvs8c9+7JTfB806NB726KvvkHie23j+0V8N+pR/NclxYpXXocA/UFZ43LWaSfb/31vH7c5IpxMrAQyEg7Gq2Fg3EaEZeRiAsFrgUFM6vwPlLAqeEFC1cYqlXzme/pwzo2XlIPJWFgL0R8w+sxctVd7c9OO7ETU2P7uhjjyfiCR8KKadzJodSE7Tu5ZcQ8glIuRR4GB7b/bHiuvtcCusoo/YUyvuHCuLRVHFfdP9hmkqSqXlnHVs/zF0z9FUAkh/8phGbl+Wm91CeyHYYedS2net2C4gBfTqcXhC23YIly8W8yJw8Mk+OJ/JGpk1h2R0GAaRn90rMKWf4sGEHvpzNS0QmE7QbdnN9npCCqq+HTzjzfxMGLKxXCaLg7bsijh4dsyM5XEVJPmEC/2RDTUzPGkDoaUtH9UJLlS0cGVgm2wGKvOPOn30mtdm6FY9Nr4Ppeb7Z+JYntP5uXhQ9II+e9U/BDyHeDiM8Ic00Yl6rrQo+yHmTyaPo0gNNn6+hUad6dHNskssXGYpFyc+qvlIm6AzgwnZWJQxUFwg4i763uv2lmVbheLLaKa2GGHmBngznXc7KxyOWOAQeipN640Wvzecx0Ta94YDYoSWpnDZwY71T9GA5d8PXEALESsDE5fp9Rzx8MnlTWjRx/+lj0AqxN6Jo89PtPBMu79i9zOag9CbVQ7E6kZv3xaJwT/L8WafMaY6wgSSCvDP+gKvAWSllDqGnAuqQJPYGfQookfh12u5izJMOsbi7fTQLIi0s+wiPIDHRlgIXjdjnwBk7mrk/j26veLHrqu0ZfGD4Hm6O/e4TX9LjAmzMMjoHMZ7UBIhimMVqMYxOaTWBs7dMUTy8dBYMOr8ijXd7/He2dY9Z8eoOEfL0zQw9QVIkXwvM8uSUUMj3YH9CjTM/cx4NC8ZopnoP7CIKJitQhu/4opvV6XeqbudQ46afPdW4Eob5hILE44oPoxuzT1R7XuySHHr5WffrnLe0RrQ9bCtrKctsM14cvlaYzyy+UhZ8lFX5vTnvHlTdhrieMvQE7qunpEl1Kl/OFDfj7Oy4c3sVSU2kbl6XUeBjjgw3cU4l7w4bZFNP0DjYw6cwTy1XDm+DSEb9CvZ25cyKqoRkJwKkZYzL+ieKTX9luO4CHZxCG2KxtlXHA3GJ4meDX5cMO/91xkAC250JL7R307u+/Ez+QjsnFkoj2fn/i/WEWe4KJ/BeMucUm/eFpOxDyYDv6J5ASyZJIV+pl6wFuAcKlDxnXUEuZ3/ukeScQ0s78vttJVI56QEBBtF6qmOdll5jg+zPoMrUL8uDprMfueY3BBDixFQhoHdcMNfwXxpNZ8SZlnnonv+vqRF/Kuogebvn9JL0yIdtP4vG5f5IpPwe8K1iX8iqkhRUefa5NwDtiyU1D95p53tH8ou/hXGw72548mHNBeLx74a22YWYYcTLDjK8yVrMNB2rt8OJFvozORrqvSVNJcvaphxs60LVEcE2NWkwYtRsNtKH88MoJJ5VpxOIxpjjn/qdcYvvbujIdqYdzE0yWXvzN4rRpsImnbwaC3o+88fcXd/x4VDf8REZm9WnkFrFPNh0G0osMGBUP72a2rPqYqygBKwZlazuwGn0o0EO9kl05Hu9MyfR06LW/4AuMMBbxf2wNFXYOMtyB82tOn8MKBOTTUaOoSRALjhVE+qwRvpXVGYfLasIu2KSoH2GLADdpVuMt7uPkSkNWbO3XdSVRS4Dmr40aGR+0d2YfoG/kYizxRFgh6owofE6pfTQt+bDGrPwISRfY90qfFb2ZVCq2nFNDXLjh0MrSc7eFK1e90roUc3VNlhF5FiwXxUFdCGYX2JpDPk1ycaOYX5mSqe9FG19kDZgG7i0Mw1cK9/HqM77z0/eZfNSjPaDKvgLCDsdkvhS/I2u35e64L9nzQgGW1Icv4cCx2G1AD4A1gCmpObNgWA24TqN4NIZH/L/vYrgnEMEPX96HtPlTna2j0Qmo7UIczFk4/DmhiOLHHLYLpV0CamruvlAba+/UWi8AV96YUHn+Q5CRh3KkTc7cUm0vmCXLtUJ26Ws1XS0GEbvig7bLGjFqk5x6JRYY7mMVb+Ypa98gFwiHAJjqcVDcqiiYd5JPtGeR8zozTBtTunfH35V/II3vtSqT5QFdkXaTjXkJxcnLPcLgCzLpjJTjifKdfhvMkSEist43oown+fotZ+DCKE5zAIkS54d1btr6fVIcunM8I7weM5O4Aa+Yy2sSsmKTJGT9vCYlWn+eErDDW/LYJ+bvfTqPYC5ZCywMK+Qa4QlhgZTeKN4hFk27pkaOAVRZuP9TYuw4cfHHzwUrw1e6FN7yRIOyMx+rjIdnXcQ+47Ot3WXBzAF+7KtdSzpu/I0vtTbmQV1Qv8ftvEI5Kqd3pGrXAFsFVxQEbdSJcOYu0zB8ZNnfbfUWVyFrLQ+zWuZlTGrHblDWa/m53i6q4wAr+55kYPz1u5Yc/kS4DSCIq4yHejsFk/DlZP6ls3Ov5KGzUbYlbIEhCsBJ+AsR9WrsHBvcEzqLudCnX/KQ313lZpqN+lQNGk4nWMpy3v1L+LZayfwVcHtRdm7QrGAxc+wz3hPfdRgOP5fBU31V2bXoJRgTEju/2dprkac7hj9hHS+7GYe8BFVq3ZKywUYhYb0s66yF0a1TtW6cfJMOFuBvgNsU4Q4s3QlyD/JsvnhCBKHspoGJ64qebmeh13CCYzcQNnSb6LrUDH7gXc3abAi1iQ1s3gwnpvzcV+aObtIpY5lNsCSQ++gLJPkXukytj8/DgKWrwD0kuC270p5Ze7dZUotQSGXueoGyV85Pdu6OqBuVEYRu8xkfgnJ8iu5OpnsJb097lp7+G0EYLryxwWDlJZI8AfT/ySE+lQeSmw5OKD1Hk6goBZu5EGX6czZ7GLD94q8jMaV7aNe8XX7VLOWbLgUeV3hq7mPAmn7Sd1+ACaaUsyDezSnLOLbDjK9/xyFHObP51Yx1u0P3fDpaItF2iRkivBgyGdtzQ8h+2tHIFaa2czJ0RiW10hwskih2XEGDpZGWUScy000p8Cw7+tS5/OAwn2e5w33SP3+AEN0A8l4bC1wts/s36pMY+FifsXVryqU8CBJWvmFMtzBF2nEOkjx6JmhkuxOeuJkO+TSkZu2PLLSGgcg9qBCrYqqn03+0woBeOHH7EsF4LpMAddrsPdq+8J0p6e+ALsuZoohck7hH33t5H4ORp0AZPlMlguJZ5vkqwdWUXAnZTXloZWVLfBVdv1omNV/lZjA9+MOK576HOo/gBhYDzZgnl4JaIfeEXDnAA9uSZuoddoFcns/UhasTqwgeCKcckVWsB9ba0d/cCT49uazLQ+aSumLsxy/oTJz9QosQMtWnGJqfU702BZtXIr1SP2GvUIhM879QCyu7BMg2bkVHQr4i2ndI6ucDloAe37MhvHrQTZB4J6R2DDciroaRtcLqPVg5GxSBKhKxxgFYesUhfFgLGA5kVQQLGzxCFIh8VjV8z8+BbkKjRYxok9ssu5+bx9zP3GlQCBiKiepmttMcaOY7hviAiX8nf6y+WxMflhtZPRSR2xMLOX2QtCdy3WLnVghVvNRK08EU8ni8q/0GY2LO+Eri/zyX4WLDdoH8uyrhUnky3ovN9zNe7fV+r9oAwjlAbqIzUCtKDyMIoeabeQ8m/COOY1dOqTqsEiIEoSEMTGwVHcLNV4SleJ0eVqGlAs3rVUbxUG8oL65suhzRii+UM5iNNtmFkZ5kH8hrHThhV12oHBbPJqfrbxykhn0HsMK4ezP8vbxgtpjpSM3jF8p2hp3WTg1t3cTgocDw786IHUCGcEtHyS4zzRAGHoGLefFpKQ7dcGT2yJwObbwFjIUXToj3hFHbnT2dZlQUPZ1Tyw6PMkNb/Q5nMBnMyatEEdqBzQIYUNM2LVa1FBs6YPMa6/C51MVviZL8cI5yxbDEQyyCN+TyQcfJXc2kyRnd5cr36QY08lMZ3adWVWCvfryAzX8fD8tNLo60a5dA3lM2wuIxHDg1qGwq7O767lBdkbeRWdLcV1GsV9+7xRDg9A41ra2NR+NtSQvu61AndaBqr7DF73RlfEzXD2cZgp0tqbCkSCCEMVDzphYq0Z/wwcD/a06TVx5YbhL7DcwGvcoUBDJ+Muwcbrs4vcfKWKoNT/IfnLltrctZN6gcbpEQxQnvmVre1lptV8Q0s2YDSVUsP9803PDfbnodg+SW2jAJS5diNZCnTO3631sMQcwzeGLcW6l23gYQqMbkQvjOlkz+9Kw/f4Ltm5FfaqC0bBUbK8dqG2qr0UrtktFuEACDqPwJvwyAFfuJ4cTnLdwyedQFGyelC2GD7noj3b3g10+GdcK/xyzwwLUmxwjEP5qforqFwfnArcEZcrc4RQ/RcPmCsp9zCTLLY49bfxFbIUKTnFeI0LccnpXWQmOL7FlGQQ7w4Bg+KFZAFVMshPR7adsrKgE0GGLMjd2cTQ4Yt3lQnCWiG2Yo+t9YSaIlmJaWhG41zP5AVPJHtLx3Eqd1RV4jULQVihhWEc2u24Lc1ciuL1YA/htDewReu5Srpl7Y1XkkW3qPsDZetYNuQ5acip5vx07Pb7QFGTcbR4312C6GXCeSj99QjFP68OaklpYC+PwRZfmxec0PjBgb9rxX0k7wOwzgAj4lFfs6DVmD8WXuhyfJ+8SDO9t3CXKordYyztOoEK+bu/gn6IeM1RyOp2hiT9/HfYjzMNfRmH/JZyEEIAoaS7EYw==\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":109,"output":572,"cacheRead":2432,"cacheWrite":0,"totalTokens":3113,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941589217,"responseId":"29CITj0nrTvaiQ1tW5mTfgaec3iZjO0ko6z/A6hdhU1Cv3Ni8pN4nNcS39UUDoSwYvGR9l3AeBhL3fxBEsty+ZnthMxBGP83mm1U7rnz9UP/9dUhpJJrBiSBZLJX0EkZR9R5wW0CGrk3VYswkGvu1YPbpBBeYJQ4Y4ASGKEmdKWlzFfExN/4LsrRKYTrqnJPu06js3L2DqYoMKZKhSWh0RoGiv7jOINGVIEVHuQCAb9YC49UWlafPKf2dAblnA58c60jlXqC4lA9YXpVr7Jc3NMrWyZQy5gxoelWl3SmuLJrxKJjfIVee9Q5TKr8ISq8FTHblFIp0/W3P3B2kcZXTgAMpWi2olgPneOvhAP8+99pzoRz0IHmzI+4qidvwB/jNIJIqSKZZfgeMaHz1/AATDZgaV9FBzMw0g=="}}
{"type":"tool_execution_start","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","args":{"command":"ls -la"}}
{"type":"tool_execution_update","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","args":{"command":"ls -la"},"partialResult":{"content":[]}}
{"type":"tool_execution_update","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","args":{"command":"ls -la"},"partialResult":{"content":[{"type":"text","text":"total 8\ndrwxr-xr-x 1 alex alex  368 Apr 11 22:00 .\ndrwxr-xr-x 1 alex alex  122 Apr 11 17:42 ..\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 adapt\n-rw-r--r-- 1 alex alex 1090 Apr 11 22:00 AGENTS.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 animate\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 arrange\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 audit\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 bolder\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 clarify\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 colorize\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 critique\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 delight\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 distill\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 extract\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 frontend-design\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 harden\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 normalize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 onboard\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 optimize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 overdrive\ndrwxr-xr-x 1 alex alex   56 Apr 11 21:56 .pi\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 polish\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 quieter\n-rw-r--r-- 1 alex alex 3664 Apr 11 22:04 SKILL.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 teach-impeccable\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 typeset\n"}],"details":{}}}
{"type":"tool_execution_end","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","result":{"content":[{"type":"text","text":"total 8\ndrwxr-xr-x 1 alex alex  368 Apr 11 22:00 .\ndrwxr-xr-x 1 alex alex  122 Apr 11 17:42 ..\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 adapt\n-rw-r--r-- 1 alex alex 1090 Apr 11 22:00 AGENTS.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 animate\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 arrange\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 audit\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 bolder\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 clarify\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 colorize\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 critique\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 delight\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 distill\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 extract\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 frontend-design\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 harden\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 normalize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 onboard\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 optimize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 overdrive\ndrwxr-xr-x 1 alex alex   56 Apr 11 21:56 .pi\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 polish\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 quieter\n-rw-r--r-- 1 alex alex 3664 Apr 11 22:04 SKILL.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 teach-impeccable\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 typeset\n"}]},"isError":false}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","content":[{"type":"text","text":"total 8\ndrwxr-xr-x 1 alex alex  368 Apr 11 22:00 .\ndrwxr-xr-x 1 alex alex  122 Apr 11 17:42 ..\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 adapt\n-rw-r--r-- 1 alex alex 1090 Apr 11 22:00 AGENTS.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 animate\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 arrange\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 audit\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 bolder\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 clarify\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 colorize\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 critique\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 delight\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 distill\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 extract\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 frontend-design\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 harden\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 normalize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 onboard\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 optimize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 overdrive\ndrwxr-xr-x 1 alex alex   56 Apr 11 21:56 .pi\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 polish\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 quieter\n-rw-r--r-- 1 alex alex 3664 Apr 11 22:04 SKILL.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 teach-impeccable\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 typeset\n"}],"isError":false,"timestamp":1775941609568}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","content":[{"type":"text","text":"total 8\ndrwxr-xr-x 1 alex alex  368 Apr 11 22:00 .\ndrwxr-xr-x 1 alex alex  122 Apr 11 17:42 ..\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 adapt\n-rw-r--r-- 1 alex alex 1090 Apr 11 22:00 AGENTS.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 animate\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 arrange\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 audit\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 bolder\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 clarify\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 colorize\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 critique\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 delight\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 distill\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 extract\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 frontend-design\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 harden\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 normalize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 onboard\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 optimize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 overdrive\ndrwxr-xr-x 1 alex alex   56 Apr 11 21:56 .pi\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 polish\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 quieter\n-rw-r--r-- 1 alex alex 3664 Apr 11 22:04 SKILL.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 teach-impeccable\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 typeset\n"}],"isError":false,"timestamp":1775941609568}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":109,"output":572,"cacheRead":2432,"cacheWrite":0,"totalTokens":3113,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941589217,"responseId":"29CITj0nrTvaiQ1tW5mTfgaec3iZjO0ko6z/A6hdhU1Cv3Ni8pN4nNcS39UUDoSwYvGR9l3AeBhL3fxBEsty+ZnthMxBGP83mm1U7rnz9UP/9dUhpJJrBiSBZLJX0EkZR9R5wW0CGrk3VYswkGvu1YPbpBBeYJQ4Y4ASGKEmdKWlzFfExN/4LsrRKYTrqnJPu06js3L2DqYoMKZKhSWh0RoGiv7jOINGVIEVHuQCAb9YC49UWlafPKf2dAblnA58c60jlXqC4lA9YXpVr7Jc3NMrWyZQy5gxoelWl3SmuLJrxKJjfIVee9Q5TKr8ISq8FTHblFIp0/W3P3B2kcZXTgAMpWi2olgPneOvhAP8+99pzoRz0IHmzI+4qidvwB/jNIJIqSKZZfgeMaHz1/AATDZgaV9FBzMw0g=="},"toolResults":[{"role":"toolResult","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","content":[{"type":"text","text":"total 8\ndrwxr-xr-x 1 alex alex  368 Apr 11 22:00 .\ndrwxr-xr-x 1 alex alex  122 Apr 11 17:42 ..\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 adapt\n-rw-r--r-- 1 alex alex 1090 Apr 11 22:00 AGENTS.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 animate\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 arrange\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 audit\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 bolder\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 clarify\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 colorize\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 critique\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 delight\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 distill\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 extract\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 frontend-design\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 harden\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 normalize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 onboard\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 optimize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 overdrive\ndrwxr-xr-x 1 alex alex   56 Apr 11 21:56 .pi\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 polish\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 quieter\n-rw-r--r-- 1 alex alex 3664 Apr 11 22:04 SKILL.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 teach-impeccable\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 typeset\n"}],"isError":false,"timestamp":1775941609568}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_end","contentIndex":0,"content":"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":1,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{},"partialJson":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{},"partialJson":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{},"partialJson":"{\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{},"partialJson":"{\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"path","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{},"partialJson":"{\"path"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{},"partialJson":"{\"path"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\":\"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":""},"partialJson":"{\"path\":\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":""},"partialJson":"{\"path\":\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"SK","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SK"},"partialJson":"{\"path\":\"SK"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SK"},"partialJson":"{\"path\":\"SK"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"ILL","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL"},"partialJson":"{\"path\":\"SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL"},"partialJson":"{\"path\":\"SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":".md","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"sO2eeZ4j1vLO8hdNTJPZbqjBt5iCpapsT3BgijZNIyZOR60wB/EszwZOIe8S1/DBir/aRDy96pmmfNStvnptWCzp71AC39edMSY2VcDSsLRMADQ0WonEpOzGcnw4qFp8+oXCqylM6icKnzFFZLaiOSjRsJMmtv81SjNArMZDIg/XHI9ARNwogjv3gfgmT+KCZxQ3O0XgpbZ9Dyq5mUH3YGSk1NVgt6FawwanZB8iyIug+0fmLyzJvthRz4zWLnI8ZXEug6ShtfM+OWma36riavNiodrUeibf/m0cfC1MBZc2SsrRyIFpUIC0HrBmsxLWEFCo6DUZvwGD4GJz16r4JVMbOTbx6bCnpe86LRKSQeNDptjJB3lKBtQ0zul5+LphjAeooWPDWQY2d2lTdg/dWp4M2S1S6zO4WLM+rAf6mC1VeS8NEdMmNqyxZ1gUg/48+MX55ZenrQao9JCR6aS3K2rh9vSKW95wEQDARLVWaht48ZG2RfKWowLkYkxMMYordxkbvSEHY1d/J0wdK3AsxMyREBb2faaYqmUd5wTQDUyNzddXqGXz6W5qTNXXBjCVbdmdpF/TnOevklkvkHblDuuDZjp8vq4qCNFro8KlgIznPeJdZlTljUNFlyKnZfP5L8+R0JfL5iZasXltCrU7MG67T7vcAz4FXPpuGQWvb/HyG3CUre6YDmwUzoapI4Qle+Q8ApVLoc8P5fhvoQlU51LH62TMd7hREopA55KvdV6lWhlI5QEgdALz56rLvR8S0t2enbsZZPm1mqsn1m+BmrcyHKBuavAmdDSL13d1l+MzXVvVIiZXpkxnko8SBnZQ0Ij2MjY+v2cZpak565uZnp6cGGWBaLbtyvlT2q8aa2f5cMpsTiqB8tYN0+ldavZSPRgU+9U3mEtjTVE0sYTaIrw0EErVfskvxVw97vkNCr4r0/mwHn+jWhfGsfwfXWz04TeLUQVn55KG5wCtEhU5pHze33KgLBeWIo5e8qrI1VOWPPIzG5nGfwZx4Vyl8rteSOouW2uTLA/XpTmjY+Cyv9Gi2FaQ3WoeYhJ1lBPE/Rryr8kz5cZd9H1GojxkblfuJSpz3YjIj9eRUlibUdeBu+B7j5CVos0XRd3v96zF7n9bScafscfcL1lPnca/efepN35YnWaRUh79YtfCx9PyX41KlTYoShb1TS55HeJ7mT5DSWFLjJIweXxB7XSdSFBgzJAoB8MMu3KRYkrjMCK8ZOIIAuy1ixYlrVXz/8YmIMiaW1DUgzDgcUxFBWa0Z+PJJ6wO2+Op4PDkgSTmIXhwDAy056HmT4gr97n4lab30pkzO89n8hWW8dmilFGvQK8JLkLbD1xbHekcAxNGGYAwuPmAFvbGggVtlsqVB5TEcThpYCQAfcsjWIFQqWVAtW6vuZWHTq22wBujY8lYkZpb5FenNdgiCiLYcpBb+H0tYuz4HCHZc7sAp/oZFVGp+MlBn3Oqp1TfQyEETZU+jddK4nhq2lViS5YvaMSFm3r00T6d81aKcUEkDnhjg80vjDDIoCDhn0+Thxx3K5XjP/Sfgu9NC/0tx4ApCLVKL7dHAzzRIZLsjcYS83VW/0Rqlv1Njk9XK4Fk1e1/v7cjjqU0tHrupudyhA8Wnc+qqY1IoOUYLIfZVCVn/fmPXWak7VtjkVUctfTv9pwIN3vqonzie5HDbH9/heK6QQVspWxOYUHCiuETovWB8AfEsyyamnppJCa+MOAl+wRyvqEIFWzn7IPQbCYxPQGbd/lOYmOBQ6PKY6J8Pw50DJpDUdslXpYjcIYi6NxIROxNlppBK4TYGXD4E9o5qqxwj3TGzrlEMPkZ4G3zc7mENPy3ylsQfupbcvNQh9b8mfLt+jpLyw3YYwsrodYO/PUrsAnTguS7mAR2DI/EvZB5bcaakLU0t/ZPtqE3Qi7pZm24fLr0fca9ETKY0KC/yqR6scmCga4+BSZ9NxLEOcu1ZLMi2v95jRtxdS9C4WMnkpbOBp8j9w+xwtNL9LwPGTSB/njLqQ4/c4r4ZSkLQ9DsFQGCpwUEuzWmMH1k/+sBBFZeAoSHlx3TH3pdcI0huQpj6DiVv47I9Tj7EGPOOnrIgqYK/lkniox7rqt5Le5g37QdNSlj1HffPIfz5fKpv46X1WZtaJ8mNf0SxmSD97ng2G4ZV625dGmw3V1Xa6N0SToGB2bT66m/T0HVMzAop+CMmshkjYtmZtf31tizxtsqrLloW6pTUHhzt56tA6tMqoOHsoaS0zi8sDEHx2ZfXgAoMYSB3+Sn8bovxbiG+qjj90cA6qAd2FnRrpBK/0D8mDX7fRbfgsVtkJegEtSkx9vYtMsAZVTWDwSazdjPCBQIR2OFp1fNu8rUV+Wg27p7LOOZPmNakx+k0Uss2CxDjB2G831uM8fANU8K8/1KNB3AP77g/d9Y0zvwtvaHUfQSqdebmwVCpHUOAv7B8MYp7e3XcXPcxUfGrQ1p4NZz8jCgnqufXnBmUIDEyGJF7Sw+z9kfrH/fUTSVHtoytB+P9eWY0/olnvN6cGu/ZBeWuB+8F7O5K7lYQRJSXczfDkZnnOfVC2jaEkIWirDSg0TypEU2TxkFuxfVWPWZ+oVomxB3MpdyMHkWBECOIVUT3Nb2IrmXR048STILX2EBG2A7HujQz3oHXki/w3JoFinVlGvfOw7DZDR5CUBL4xOsbbHSFPpaBRgpTHrJNDJUCLBAEkh7uk+xl9uM0mgocni9cuwnBrB+mwZoDA99XwKbx2c4qwap3enTIZd8mlxpGMFI5/WYnN4Az8Ib5OAglutO81FZE7d1pNHrE7tG/tiwVNsZshmI+iDI6HVOVcjEcicKLkNsFegONLPtbqTqobFQjxPzEKDaAr8gbm9QzT51D6D8hMMV055Mjv3OEvlO9jYulFrgmXUEjsF4baXUak2D8RgnQGtMUl/S9Vg1uylqKqfuADyHbdOD0XyqQLhcVtSPX1bZ0oHgKlFDQtWvoRRzWbm/TK9IBmO9sBAI1feTrr5LWnLnTvB83Cp9Q2Pnn+NLkyPqV0owTjOaJ3h/V3z810vipmbLdTNepTNlBcK7apyNUkWeCr1Dt3zQydOMQZT4KgV93Ax3qiSmmDWn9hqka0YBRAWvtSiO2IZaukO+bxysUUYSMq+OV7usunZHFrnCSUgjH38Jq6LMCgpesfV+X+OHKxMa97MiGvsAdkFgOxEXUgF8SyMKDTg+993t2QbE3osWiH+8o0rq1jbXA9uze9s0NTt6H5fmUFrehAyJvcxVWKGSFoTVOfZ6DFuF8jTgDTqrrqui5ooz0+i6pGWSn8lFZePFtW5nwjIp8hIStvkkiZS8PH2bAm49St2QQwfqJMUQMoJICm557vzVrFQQ5XYU+qJcuw4YfhakA0jEN2gtNOl6rF3BjgZE53DVPKPei/FKC8szxjWMaB73NH4eXbPCSicljBeYZAeJbImn7jjbYQOMflUWv4YdNUexfHXIM5VcYp8431COOHNsf91ysHn5wHIrbwDSozWca8nzETiVRDIkvxSyBMXDibxCeA8WyPwdBsXVi1KSj4Fa+ZFeLw/MZsH3RLz1YKNB95cWlUE9Hk1bSAAUWPPDQvQ0YO86FOv6iagKLGgFrc6ekzClSi/dexi0EMpJBWK8pivbmbu0xbQ5z0U049/H7KRFONM89JsSKq5TkmGCnvWyf6NPDFG3Te/C2g4iXvewOvCZ7lDilQL6mew4+0995J9z0cBhryaZmYp1ePlG/O30uh+4B4AxSLOGQ7bs8iiMgvS73vM1eHzRd0PRaAuNrbgg1wdBapnbPNGCprVW+1s3vlLKEu9JzoNnIJtGu4KRo4NgwtbGuGabcH93QjBzaLyDPDNSCYQt4dl77XeFPD7WLvQoJdGTL/BJOruXyzTZNXkc7KFW9DZ9AF0Jm2YVpcoedXgyFRy/uBRBI+f8s2WxrYdQbJbJoK4fBWoQVHq7LI3dipH8aIUeeexlKNiRcNBWZDwCVshFsEj5EELaGX44UndUZR5OgnMMIn45ShiJnkyHeohQPYQ0tGs+E6BU6fPXkYNw+Tmcc5THJ1qbvtngnBMUI+dJkN+m7Dt7gcIm9/nGP9VGdB0PM5xdc2wih6U8QZW1DO6xQs2HhMzMjX+gl7mevOvw7l7YqNq11rinpDqQlIzJCEUdb8T1Y5C+29HLGwpgmWL6Uw0vrpYhkctqQVkYv8zSFAjGxmIxqdCdF+bU6jfZUSfj7klqNVrxSxLEhjVcrZxEHe7czbW1QSnHTBn+wOSF0BZ+3CKQ24t8dUTm3WYhGr6PQC9N8yjqUPbZ7TIZoCqYXLExgNgb3bY9fMphT3UbZ21wm42xQ2b3WBuvJE6ERX0TBJJR4M93t+jzjRrGDrgDYtaD6g7wZ+HgE5LfOmf8wZywcytEx21SFb6aG6SRLHWx2w519H5YwILWDxbOBb4YiSqebLAQ/MnhbLNvxenxDf4/f/Tmg00oFxhFqvV9UU1jDDjm5jgtS5YgRIO4VNelWTUbE7BSrgsiQvcCwwEQ6aXz9N6RdTJcR0+Jq2PZd89MP6hGRzJcYnTMIYMJWvdMpOjh5VGr3+x4ap+6WokGEXZdJ5JOmU3AvGGLMQf51CJm+nU1pfP9Ui897/NihVXp4GR6a9Ter00TZhUJBCW179OB7splC8gdRtpc9eqz0lZ89bY6WhoCTucqRY6qLj/MQXJz2YTBaBkGtVT66b1C6wIG4nifHYFawjhISj6iwNCoI30pIxfXmbB7OYn85i/tzfTUrOHqP/uyg+CX2vvgWlETxjNB2hknC776OHNT00uzXxZ6IJ5HWfgGyD81I/PnYB3BUVv8O++dsw1yp8sBX7hYdyyYXu2N2yuEWFEw/V+3/4ToPx05o6QaUNH3xSrOLOQ8wn0g6oVSBcKKqPLAyrpgC9HPxFQ/Q4fvYfEjhOZlxCijhmQ14XE4s9XsC+FKPXYMdStb7g5b8CvMc3RxxSQ9KMjhA96/F4A0ieVYPEDKcc2dyN8ErolRxz0vD3irxYBbnTPW7g0BNE3OS9HXTVo=\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"sO2eeZ4j1vLO8hdNTJPZbqjBt5iCpapsT3BgijZNIyZOR60wB/EszwZOIe8S1/DBir/aRDy96pmmfNStvnptWCzp71AC39edMSY2VcDSsLRMADQ0WonEpOzGcnw4qFp8+oXCqylM6icKnzFFZLaiOSjRsJMmtv81SjNArMZDIg/XHI9ARNwogjv3gfgmT+KCZxQ3O0XgpbZ9Dyq5mUH3YGSk1NVgt6FawwanZB8iyIug+0fmLyzJvthRz4zWLnI8ZXEug6ShtfM+OWma36riavNiodrUeibf/m0cfC1MBZc2SsrRyIFpUIC0HrBmsxLWEFCo6DUZvwGD4GJz16r4JVMbOTbx6bCnpe86LRKSQeNDptjJB3lKBtQ0zul5+LphjAeooWPDWQY2d2lTdg/dWp4M2S1S6zO4WLM+rAf6mC1VeS8NEdMmNqyxZ1gUg/48+MX55ZenrQao9JCR6aS3K2rh9vSKW95wEQDARLVWaht48ZG2RfKWowLkYkxMMYordxkbvSEHY1d/J0wdK3AsxMyREBb2faaYqmUd5wTQDUyNzddXqGXz6W5qTNXXBjCVbdmdpF/TnOevklkvkHblDuuDZjp8vq4qCNFro8KlgIznPeJdZlTljUNFlyKnZfP5L8+R0JfL5iZasXltCrU7MG67T7vcAz4FXPpuGQWvb/HyG3CUre6YDmwUzoapI4Qle+Q8ApVLoc8P5fhvoQlU51LH62TMd7hREopA55KvdV6lWhlI5QEgdALz56rLvR8S0t2enbsZZPm1mqsn1m+BmrcyHKBuavAmdDSL13d1l+MzXVvVIiZXpkxnko8SBnZQ0Ij2MjY+v2cZpak565uZnp6cGGWBaLbtyvlT2q8aa2f5cMpsTiqB8tYN0+ldavZSPRgU+9U3mEtjTVE0sYTaIrw0EErVfskvxVw97vkNCr4r0/mwHn+jWhfGsfwfXWz04TeLUQVn55KG5wCtEhU5pHze33KgLBeWIo5e8qrI1VOWPPIzG5nGfwZx4Vyl8rteSOouW2uTLA/XpTmjY+Cyv9Gi2FaQ3WoeYhJ1lBPE/Rryr8kz5cZd9H1GojxkblfuJSpz3YjIj9eRUlibUdeBu+B7j5CVos0XRd3v96zF7n9bScafscfcL1lPnca/efepN35YnWaRUh79YtfCx9PyX41KlTYoShb1TS55HeJ7mT5DSWFLjJIweXxB7XSdSFBgzJAoB8MMu3KRYkrjMCK8ZOIIAuy1ixYlrVXz/8YmIMiaW1DUgzDgcUxFBWa0Z+PJJ6wO2+Op4PDkgSTmIXhwDAy056HmT4gr97n4lab30pkzO89n8hWW8dmilFGvQK8JLkLbD1xbHekcAxNGGYAwuPmAFvbGggVtlsqVB5TEcThpYCQAfcsjWIFQqWVAtW6vuZWHTq22wBujY8lYkZpb5FenNdgiCiLYcpBb+H0tYuz4HCHZc7sAp/oZFVGp+MlBn3Oqp1TfQyEETZU+jddK4nhq2lViS5YvaMSFm3r00T6d81aKcUEkDnhjg80vjDDIoCDhn0+Thxx3K5XjP/Sfgu9NC/0tx4ApCLVKL7dHAzzRIZLsjcYS83VW/0Rqlv1Njk9XK4Fk1e1/v7cjjqU0tHrupudyhA8Wnc+qqY1IoOUYLIfZVCVn/fmPXWak7VtjkVUctfTv9pwIN3vqonzie5HDbH9/heK6QQVspWxOYUHCiuETovWB8AfEsyyamnppJCa+MOAl+wRyvqEIFWzn7IPQbCYxPQGbd/lOYmOBQ6PKY6J8Pw50DJpDUdslXpYjcIYi6NxIROxNlppBK4TYGXD4E9o5qqxwj3TGzrlEMPkZ4G3zc7mENPy3ylsQfupbcvNQh9b8mfLt+jpLyw3YYwsrodYO/PUrsAnTguS7mAR2DI/EvZB5bcaakLU0t/ZPtqE3Qi7pZm24fLr0fca9ETKY0KC/yqR6scmCga4+BSZ9NxLEOcu1ZLMi2v95jRtxdS9C4WMnkpbOBp8j9w+xwtNL9LwPGTSB/njLqQ4/c4r4ZSkLQ9DsFQGCpwUEuzWmMH1k/+sBBFZeAoSHlx3TH3pdcI0huQpj6DiVv47I9Tj7EGPOOnrIgqYK/lkniox7rqt5Le5g37QdNSlj1HffPIfz5fKpv46X1WZtaJ8mNf0SxmSD97ng2G4ZV625dGmw3V1Xa6N0SToGB2bT66m/T0HVMzAop+CMmshkjYtmZtf31tizxtsqrLloW6pTUHhzt56tA6tMqoOHsoaS0zi8sDEHx2ZfXgAoMYSB3+Sn8bovxbiG+qjj90cA6qAd2FnRrpBK/0D8mDX7fRbfgsVtkJegEtSkx9vYtMsAZVTWDwSazdjPCBQIR2OFp1fNu8rUV+Wg27p7LOOZPmNakx+k0Uss2CxDjB2G831uM8fANU8K8/1KNB3AP77g/d9Y0zvwtvaHUfQSqdebmwVCpHUOAv7B8MYp7e3XcXPcxUfGrQ1p4NZz8jCgnqufXnBmUIDEyGJF7Sw+z9kfrH/fUTSVHtoytB+P9eWY0/olnvN6cGu/ZBeWuB+8F7O5K7lYQRJSXczfDkZnnOfVC2jaEkIWirDSg0TypEU2TxkFuxfVWPWZ+oVomxB3MpdyMHkWBECOIVUT3Nb2IrmXR048STILX2EBG2A7HujQz3oHXki/w3JoFinVlGvfOw7DZDR5CUBL4xOsbbHSFPpaBRgpTHrJNDJUCLBAEkh7uk+xl9uM0mgocni9cuwnBrB+mwZoDA99XwKbx2c4qwap3enTIZd8mlxpGMFI5/WYnN4Az8Ib5OAglutO81FZE7d1pNHrE7tG/tiwVNsZshmI+iDI6HVOVcjEcicKLkNsFegONLPtbqTqobFQjxPzEKDaAr8gbm9QzT51D6D8hMMV055Mjv3OEvlO9jYulFrgmXUEjsF4baXUak2D8RgnQGtMUl/S9Vg1uylqKqfuADyHbdOD0XyqQLhcVtSPX1bZ0oHgKlFDQtWvoRRzWbm/TK9IBmO9sBAI1feTrr5LWnLnTvB83Cp9Q2Pnn+NLkyPqV0owTjOaJ3h/V3z810vipmbLdTNepTNlBcK7apyNUkWeCr1Dt3zQydOMQZT4KgV93Ax3qiSmmDWn9hqka0YBRAWvtSiO2IZaukO+bxysUUYSMq+OV7usunZHFrnCSUgjH38Jq6LMCgpesfV+X+OHKxMa97MiGvsAdkFgOxEXUgF8SyMKDTg+993t2QbE3osWiH+8o0rq1jbXA9uze9s0NTt6H5fmUFrehAyJvcxVWKGSFoTVOfZ6DFuF8jTgDTqrrqui5ooz0+i6pGWSn8lFZePFtW5nwjIp8hIStvkkiZS8PH2bAm49St2QQwfqJMUQMoJICm557vzVrFQQ5XYU+qJcuw4YfhakA0jEN2gtNOl6rF3BjgZE53DVPKPei/FKC8szxjWMaB73NH4eXbPCSicljBeYZAeJbImn7jjbYQOMflUWv4YdNUexfHXIM5VcYp8431COOHNsf91ysHn5wHIrbwDSozWca8nzETiVRDIkvxSyBMXDibxCeA8WyPwdBsXVi1KSj4Fa+ZFeLw/MZsH3RLz1YKNB95cWlUE9Hk1bSAAUWPPDQvQ0YO86FOv6iagKLGgFrc6ekzClSi/dexi0EMpJBWK8pivbmbu0xbQ5z0U049/H7KRFONM89JsSKq5TkmGCnvWyf6NPDFG3Te/C2g4iXvewOvCZ7lDilQL6mew4+0995J9z0cBhryaZmYp1ePlG/O30uh+4B4AxSLOGQ7bs8iiMgvS73vM1eHzRd0PRaAuNrbgg1wdBapnbPNGCprVW+1s3vlLKEu9JzoNnIJtGu4KRo4NgwtbGuGabcH93QjBzaLyDPDNSCYQt4dl77XeFPD7WLvQoJdGTL/BJOruXyzTZNXkc7KFW9DZ9AF0Jm2YVpcoedXgyFRy/uBRBI+f8s2WxrYdQbJbJoK4fBWoQVHq7LI3dipH8aIUeeexlKNiRcNBWZDwCVshFsEj5EELaGX44UndUZR5OgnMMIn45ShiJnkyHeohQPYQ0tGs+E6BU6fPXkYNw+Tmcc5THJ1qbvtngnBMUI+dJkN+m7Dt7gcIm9/nGP9VGdB0PM5xdc2wih6U8QZW1DO6xQs2HhMzMjX+gl7mevOvw7l7YqNq11rinpDqQlIzJCEUdb8T1Y5C+29HLGwpgmWL6Uw0vrpYhkctqQVkYv8zSFAjGxmIxqdCdF+bU6jfZUSfj7klqNVrxSxLEhjVcrZxEHe7czbW1QSnHTBn+wOSF0BZ+3CKQ24t8dUTm3WYhGr6PQC9N8yjqUPbZ7TIZoCqYXLExgNgb3bY9fMphT3UbZ21wm42xQ2b3WBuvJE6ERX0TBJJR4M93t+jzjRrGDrgDYtaD6g7wZ+HgE5LfOmf8wZywcytEx21SFb6aG6SRLHWx2w519H5YwILWDxbOBb4YiSqebLAQ/MnhbLNvxenxDf4/f/Tmg00oFxhFqvV9UU1jDDjm5jgtS5YgRIO4VNelWTUbE7BSrgsiQvcCwwEQ6aXz9N6RdTJcR0+Jq2PZd89MP6hGRzJcYnTMIYMJWvdMpOjh5VGr3+x4ap+6WokGEXZdJ5JOmU3AvGGLMQf51CJm+nU1pfP9Ui897/NihVXp4GR6a9Ter00TZhUJBCW179OB7splC8gdRtpc9eqz0lZ89bY6WhoCTucqRY6qLj/MQXJz2YTBaBkGtVT66b1C6wIG4nifHYFawjhISj6iwNCoI30pIxfXmbB7OYn85i/tzfTUrOHqP/uyg+CX2vvgWlETxjNB2hknC776OHNT00uzXxZ6IJ5HWfgGyD81I/PnYB3BUVv8O++dsw1yp8sBX7hYdyyYXu2N2yuEWFEw/V+3/4ToPx05o6QaUNH3xSrOLOQ8wn0g6oVSBcKKqPLAyrpgC9HPxFQ/Q4fvYfEjhOZlxCijhmQ14XE4s9XsC+FKPXYMdStb7g5b8CvMc3RxxSQ9KMjhA96/F4A0ieVYPEDKcc2dyN8ErolRxz0vD3irxYBbnTPW7g0BNE3OS9HXTVo=\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":1,"toolCall":{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Swv4On0Bt4YldR6yPJS5NRwSayeE4jVIvCh+Trb/dR4Z9tCcF2VzS77IhWrGr52LaIAEP97U8DqORqKb2e9AjpcORrPN8+3P14u2apIBZSSjjWGM1uwgaUEwfQ2q1YqD8q3iOJS9UQEEF7TvMxb0HS/RtH8XauPmd4B5LF7DKOal3usMAfBtVXEIDxYz+u2+cU45sgbsW+zkKfuXomOqcLMewju8ra1HD3YPQmnxg13CJ794R+Dcdrbc8ELzeSyxMiFb/8A2rACjRhvyFEbZ5WdvBY8JLdEy+6M6kH9VOAYLllkRMt+etVmJ6iFwbjWAlLqJnvRzkl6pEcsJSibK0L5Uj7u/hteSfNYB4krfJjFMfXxOEAZJeYhjhhfEUuCEv54X0MDoZRVrWyHjPhwe3ypSrSXQnOM=","name":"read","arguments":{"path":"SKILL.md"}},"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941609573,"responseId":"puL215YXvpmvKqVteCP364gMX1LS+DjCP0F8Ffr8TWpnmiu1BSzKp/vEjaDVwdhmXHIZH8vnm5mB4Kz2XPxhzOsOltWuZX1+yqzmdv5SaLPq8+7AorsZccl5oN/wl9L1m4cBSj+mFtzFZ5tR7b4prUj89K16/2sUJSgh9hUId3uRvdhKwNe5QESBcbY67ii7lF0217Vg3zbmjNu/JBXBvJs46fq57PwTbVzsExu9Y9t/+KZzvCJqBmKdjnrOueUnbWs3zo58mogSr0N2V+QaXHvx1MBlez19pqyCWnpa3cuIXNoYXXTf2ObrL2KIQCSlNPXHTUeA4YRSWaQi1vfApatHByGAyW7gdpeZfcc9HldAuk/VdCjm3Pw3zGd5/A0zPyF00CACO07ET6Z5uRwHLCU7rEdpvL4k9A=="}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":1397,"output":456,"cacheRead":2432,"cacheWrite":0,"totalTokens":4285,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941609573,"responseId":"DAavDSBAP1TFdtcwYxwuLKIE7bLxUKoOcxxUeljfA+gF+oV7bzBAfOk7YdbQqeiSBFrHJznJATEqLmt4YszSOqT6glHJSieds1Jy9UVm3dLfWijxSCsR5FGwn/ueeotrAcWa4jDaJyRgx5VAjws88h6IYx3ZEUjl73oopuWmw5nudoYvGZoIco6eN4nA19yGCfX+URtCIbqPmhgP+Vj4XqXmTkauucj0ODDwghvga9uLBvys8LrSYI7ztoY0IKJ5g7YrImSRUubRa8DC1pjVLP5Vop35dkkL+ltSBRFJEljTCb0UKX5zRwdFw5rZmJbGPXCtP7yqN+5CmNDGPz3yELU6mw4sDslkusOr8GgflnOM8o8KMIhCZAZYTMiuqwVA+JwAOg0cvsc3KSJSSSA1VRlK3ib2peLhhg=="}}
{"type":"tool_execution_start","toolCallId":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","toolName":"read","args":{"path":"SKILL.md"}}
{"type":"tool_execution_end","toolCallId":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","toolName":"read","result":{"content":[{"type":"text","text":"---\nname: frontend\ndescription: Use when a task touches frontend UI/UX/design quality and the agent needs to choose which specialized frontend skill or combination of skills to load from this frontend skill pack.\n---\n\n# Frontend Skill Router\n\nPick the smallest set that matches the job.\n\n## First checks\n\n1. **Net-new UI or major visual direction work** → use `frontend-design`.\n2. **No design context yet** and chosen skill says to invoke `frontend-design` → run `teach-impeccable` first if instructions and `.impeccable.md` do not already contain design context.\n3. **If a chosen skill requires `frontend-design`, load it first. Do not skip it. Do not place it later in the sequence.**\n4. **If a skill's own doc has mandatory prep, follow it.**\n\nSkills that must route through `frontend-design`: `adapt`, `animate`, `arrange`, `audit`, `bolder`, `clarify`, `colorize`, `critique`, `delight`, `distill`, `normalize`, `onboard`, `overdrive`, `polish`, `quieter`, `typeset`.\n\n## Choose by primary need\n\n| Need | Skill |\n|---|---|\n| Build or redesign distinctive UI | `frontend-design` |\n| Gather persistent design context once | `teach-impeccable` |\n| Review UX/design quality | `critique` |\n| Review technical UI quality: a11y, perf, theming, responsive | `audit` |\n| Fix layout, spacing, hierarchy, composition | `arrange` |\n| Improve typography and readability | `typeset` |\n| Simplify, declutter, remove noise | `distill` |\n| Tone down intensity without removing quality | `quieter` |\n| Add color, warmth, palette energy | `colorize` |\n| Make safe/bland UI more striking | `bolder` |\n| Add joy, charm, personality | `delight` |\n| Add purposeful motion and micro-interactions | `animate` |\n| Push into technically ambitious wow-factor | `overdrive` |\n| Improve onboarding, empty states, first-run flow | `onboard` |\n| Fix labels, errors, helper text, instructions | `clarify` |\n| Adapt for mobile, breakpoints, devices, contexts | `adapt` |\n| Fix speed, jank, rendering, bundle/image cost | `optimize` |\n| Fix resilience: errors, overflow, i18n, bad data | `harden` |\n| Bring drifted UI back to system standards | `normalize` |\n| Extract reusable components/tokens/patterns | `extract` |\n| Final fit-and-finish before ship | `polish` |\n\n## Common confusions\n\n- `critique` vs `audit` → design judgment vs measurable implementation quality.\n- `arrange` vs `polish` → structural layout pass vs final detail pass.\n- `distill` vs `quieter` → remove complexity vs reduce visual intensity.\n- `delight` vs `animate` → personality/joy vs motion mechanics.\n- `normalize` vs `extract` → align to existing system vs create shared system assets.\n- `bolder` vs `colorize` → stronger overall impact vs specifically more chroma.\n- `optimize` vs `harden` → speed/smoothness vs resilience/edge cases.\n\n## Common combos\n\n- New feature: `frontend-design` → specialist skill(s) → `polish`\n- UX + technical review: `frontend-design` → `critique` + `audit`\n- Busy screen cleanup: `frontend-design` → `distill` + `arrange`, add `quieter` if still loud\n- Repeated patterns + token drift: `extract` + `normalize`\n- First-run experience: `frontend-design` → `onboard`, add `clarify`, `delight`, or `polish` only if explicitly needed\n\n## Routing discipline\n\n- Choose **1 primary skill** from the user's explicit ask.\n- Add specialists only for clearly stated extra concerns or mandatory prep.\n- Do **not** add speculative helpers just because they might help.\n- `audit` is for review/check requests, not default build or refactor work.\n- `polish` is for explicit final-pass or finishing-touch requests.\n- `typeset` is for explicit typography/readability issues.\n"}]},"isError":false}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","toolName":"read","content":[{"type":"text","text":"---\nname: frontend\ndescription: Use when a task touches frontend UI/UX/design quality and the agent needs to choose which specialized frontend skill or combination of skills to load from this frontend skill pack.\n---\n\n# Frontend Skill Router\n\nPick the smallest set that matches the job.\n\n## First checks\n\n1. **Net-new UI or major visual direction work** → use `frontend-design`.\n2. **No design context yet** and chosen skill says to invoke `frontend-design` → run `teach-impeccable` first if instructions and `.impeccable.md` do not already contain design context.\n3. **If a chosen skill requires `frontend-design`, load it first. Do not skip it. Do not place it later in the sequence.**\n4. **If a skill's own doc has mandatory prep, follow it.**\n\nSkills that must route through `frontend-design`: `adapt`, `animate`, `arrange`, `audit`, `bolder`, `clarify`, `colorize`, `critique`, `delight`, `distill`, `normalize`, `onboard`, `overdrive`, `polish`, `quieter`, `typeset`.\n\n## Choose by primary need\n\n| Need | Skill |\n|---|---|\n| Build or redesign distinctive UI | `frontend-design` |\n| Gather persistent design context once | `teach-impeccable` |\n| Review UX/design quality | `critique` |\n| Review technical UI quality: a11y, perf, theming, responsive | `audit` |\n| Fix layout, spacing, hierarchy, composition | `arrange` |\n| Improve typography and readability | `typeset` |\n| Simplify, declutter, remove noise | `distill` |\n| Tone down intensity without removing quality | `quieter` |\n| Add color, warmth, palette energy | `colorize` |\n| Make safe/bland UI more striking | `bolder` |\n| Add joy, charm, personality | `delight` |\n| Add purposeful motion and micro-interactions | `animate` |\n| Push into technically ambitious wow-factor | `overdrive` |\n| Improve onboarding, empty states, first-run flow | `onboard` |\n| Fix labels, errors, helper text, instructions | `clarify` |\n| Adapt for mobile, breakpoints, devices, contexts | `adapt` |\n| Fix speed, jank, rendering, bundle/image cost | `optimize` |\n| Fix resilience: errors, overflow, i18n, bad data | `harden` |\n| Bring drifted UI back to system standards | `normalize` |\n| Extract reusable components/tokens/patterns | `extract` |\n| Final fit-and-finish before ship | `polish` |\n\n## Common confusions\n\n- `critique` vs `audit` → design judgment vs measurable implementation quality.\n- `arrange` vs `polish` → structural layout pass vs final detail pass.\n- `distill` vs `quieter` → remove complexity vs reduce visual intensity.\n- `delight` vs `animate` → personality/joy vs motion mechanics.\n- `normalize` vs `extract` → align to existing system vs create shared system assets.\n- `bolder` vs `colorize` → stronger overall impact vs specifically more chroma.\n- `optimize` vs `harden` → speed/smoothness vs resilience/edge cases.\n\n## Common combos\n\n- New feature: `frontend-design` → specialist skill(s) → `polish`\n- UX + technical review: `frontend-design` → `critique` + `audit`\n- Busy screen cleanup: `frontend-design` → `distill` + `arrange`, add `quieter` if still loud\n- Repeated patterns + token drift: `extract` + `normalize`\n- First-run experience: `frontend-design` → `onboard`, add `clarify`, `delight`, or `polish` only if explicitly needed\n\n## Routing discipline\n\n- Choose **1 primary skill** from the user's explicit ask.\n- Add specialists only for clearly stated extra concerns or mandatory prep.\n- Do **not** add speculative helpers just because they might help.\n- `audit` is for review/check requests, not default build or refactor work.\n- `polish` is for explicit final-pass or finishing-touch requests.\n- `typeset` is for explicit typography/readability issues.\n"}],"isError":false,"timestamp":1775941622780}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","toolName":"read","content":[{"type":"text","text":"---\nname: frontend\ndescription: Use when a task touches frontend UI/UX/design quality and the agent needs to choose which specialized frontend skill or combination of skills to load from this frontend skill pack.\n---\n\n# Frontend Skill Router\n\nPick the smallest set that matches the job.\n\n## First checks\n\n1. **Net-new UI or major visual direction work** → use `frontend-design`.\n2. **No design context yet** and chosen skill says to invoke `frontend-design` → run `teach-impeccable` first if instructions and `.impeccable.md` do not already contain design context.\n3. **If a chosen skill requires `frontend-design`, load it first. Do not skip it. Do not place it later in the sequence.**\n4. **If a skill's own doc has mandatory prep, follow it.**\n\nSkills that must route through `frontend-design`: `adapt`, `animate`, `arrange`, `audit`, `bolder`, `clarify`, `colorize`, `critique`, `delight`, `distill`, `normalize`, `onboard`, `overdrive`, `polish`, `quieter`, `typeset`.\n\n## Choose by primary need\n\n| Need | Skill |\n|---|---|\n| Build or redesign distinctive UI | `frontend-design` |\n| Gather persistent design context once | `teach-impeccable` |\n| Review UX/design quality | `critique` |\n| Review technical UI quality: a11y, perf, theming, responsive | `audit` |\n| Fix layout, spacing, hierarchy, composition | `arrange` |\n| Improve typography and readability | `typeset` |\n| Simplify, declutter, remove noise | `distill` |\n| Tone down intensity without removing quality | `quieter` |\n| Add color, warmth, palette energy | `colorize` |\n| Make safe/bland UI more striking | `bolder` |\n| Add joy, charm, personality | `delight` |\n| Add purposeful motion and micro-interactions | `animate` |\n| Push into technically ambitious wow-factor | `overdrive` |\n| Improve onboarding, empty states, first-run flow | `onboard` |\n| Fix labels, errors, helper text, instructions | `clarify` |\n| Adapt for mobile, breakpoints, devices, contexts | `adapt` |\n| Fix speed, jank, rendering, bundle/image cost | `optimize` |\n| Fix resilience: errors, overflow, i18n, bad data | `harden` |\n| Bring drifted UI back to system standards | `normalize` |\n| Extract reusable components/tokens/patterns | `extract` |\n| Final fit-and-finish before ship | `polish` |\n\n## Common confusions\n\n- `critique` vs `audit` → design judgment vs measurable implementation quality.\n- `arrange` vs `polish` → structural layout pass vs final detail pass.\n- `distill` vs `quieter` → remove complexity vs reduce visual intensity.\n- `delight` vs `animate` → personality/joy vs motion mechanics.\n- `normalize` vs `extract` → align to existing system vs create shared system assets.\n- `bolder` vs `colorize` → stronger overall impact vs specifically more chroma.\n- `optimize` vs `harden` → speed/smoothness vs resilience/edge cases.\n\n## Common combos\n\n- New feature: `frontend-design` → specialist skill(s) → `polish`\n- UX + technical review: `frontend-design` → `critique` + `audit`\n- Busy screen cleanup: `frontend-design` → `distill` + `arrange`, add `quieter` if still loud\n- Repeated patterns + token drift: `extract` + `normalize`\n- First-run experience: `frontend-design` → `onboard`, add `clarify`, `delight`, or `polish` only if explicitly needed\n\n## Routing discipline\n\n- Choose **1 primary skill** from the user's explicit ask.\n- Add specialists only for clearly stated extra concerns or mandatory prep.\n- Do **not** add speculative helpers just because they might help.\n- `audit` is for review/check requests, not default build or refactor work.\n- `polish` is for explicit final-pass or finishing-touch requests.\n- `typeset` is for explicit typography/readability issues.\n"}],"isError":false,"timestamp":1775941622780}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":1397,"output":456,"cacheRead":2432,"cacheWrite":0,"totalTokens":4285,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941609573,"responseId":"DAavDSBAP1TFdtcwYxwuLKIE7bLxUKoOcxxUeljfA+gF+oV7bzBAfOk7YdbQqeiSBFrHJznJATEqLmt4YszSOqT6glHJSieds1Jy9UVm3dLfWijxSCsR5FGwn/ueeotrAcWa4jDaJyRgx5VAjws88h6IYx3ZEUjl73oopuWmw5nudoYvGZoIco6eN4nA19yGCfX+URtCIbqPmhgP+Vj4XqXmTkauucj0ODDwghvga9uLBvys8LrSYI7ztoY0IKJ5g7YrImSRUubRa8DC1pjVLP5Vop35dkkL+ltSBRFJEljTCb0UKX5zRwdFw5rZmJbGPXCtP7yqN+5CmNDGPz3yELU6mw4sDslkusOr8GgflnOM8o8KMIhCZAZYTMiuqwVA+JwAOg0cvsc3KSJSSSA1VRlK3ib2peLhhg=="},"toolResults":[{"role":"toolResult","toolCallId":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","toolName":"read","content":[{"type":"text","text":"---\nname: frontend\ndescription: Use when a task touches frontend UI/UX/design quality and the agent needs to choose which specialized frontend skill or combination of skills to load from this frontend skill pack.\n---\n\n# Frontend Skill Router\n\nPick the smallest set that matches the job.\n\n## First checks\n\n1. **Net-new UI or major visual direction work** → use `frontend-design`.\n2. **No design context yet** and chosen skill says to invoke `frontend-design` → run `teach-impeccable` first if instructions and `.impeccable.md` do not already contain design context.\n3. **If a chosen skill requires `frontend-design`, load it first. Do not skip it. Do not place it later in the sequence.**\n4. **If a skill's own doc has mandatory prep, follow it.**\n\nSkills that must route through `frontend-design`: `adapt`, `animate`, `arrange`, `audit`, `bolder`, `clarify`, `colorize`, `critique`, `delight`, `distill`, `normalize`, `onboard`, `overdrive`, `polish`, `quieter`, `typeset`.\n\n## Choose by primary need\n\n| Need | Skill |\n|---|---|\n| Build or redesign distinctive UI | `frontend-design` |\n| Gather persistent design context once | `teach-impeccable` |\n| Review UX/design quality | `critique` |\n| Review technical UI quality: a11y, perf, theming, responsive | `audit` |\n| Fix layout, spacing, hierarchy, composition | `arrange` |\n| Improve typography and readability | `typeset` |\n| Simplify, declutter, remove noise | `distill` |\n| Tone down intensity without removing quality | `quieter` |\n| Add color, warmth, palette energy | `colorize` |\n| Make safe/bland UI more striking | `bolder` |\n| Add joy, charm, personality | `delight` |\n| Add purposeful motion and micro-interactions | `animate` |\n| Push into technically ambitious wow-factor | `overdrive` |\n| Improve onboarding, empty states, first-run flow | `onboard` |\n| Fix labels, errors, helper text, instructions | `clarify` |\n| Adapt for mobile, breakpoints, devices, contexts | `adapt` |\n| Fix speed, jank, rendering, bundle/image cost | `optimize` |\n| Fix resilience: errors, overflow, i18n, bad data | `harden` |\n| Bring drifted UI back to system standards | `normalize` |\n| Extract reusable components/tokens/patterns | `extract` |\n| Final fit-and-finish before ship | `polish` |\n\n## Common confusions\n\n- `critique` vs `audit` → design judgment vs measurable implementation quality.\n- `arrange` vs `polish` → structural layout pass vs final detail pass.\n- `distill` vs `quieter` → remove complexity vs reduce visual intensity.\n- `delight` vs `animate` → personality/joy vs motion mechanics.\n- `normalize` vs `extract` → align to existing system vs create shared system assets.\n- `bolder` vs `colorize` → stronger overall impact vs specifically more chroma.\n- `optimize` vs `harden` → speed/smoothness vs resilience/edge cases.\n\n## Common combos\n\n- New feature: `frontend-design` → specialist skill(s) → `polish`\n- UX + technical review: `frontend-design` → `critique` + `audit`\n- Busy screen cleanup: `frontend-design` → `distill` + `arrange`, add `quieter` if still loud\n- Repeated patterns + token drift: `extract` + `normalize`\n- First-run experience: `frontend-design` → `onboard`, add `clarify`, `delight`, or `polish` only if explicitly needed\n\n## Routing discipline\n\n- Choose **1 primary skill** from the user's explicit ask.\n- Add specialists only for clearly stated extra concerns or mandatory prep.\n- Do **not** add speculative helpers just because they might help.\n- `audit` is for review/check requests, not default build or refactor work.\n- `polish` is for explicit final-pass or finishing-touch requests.\n- `typeset` is for explicit typography/readability issues.\n"}],"isError":false,"timestamp":1775941622780}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_end","contentIndex":0,"content":"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":1,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":"{\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":"{\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"path","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":"{\"path"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":"{\"path"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"XOfe0qcBg65oslwQ9Yfsz+TARJiOn6e46rZwDqrMsCnqUydY1m15gP1I0cxRRpV2Mt448UNcnLuDnZkY4R+DcHvUkIItDuE8eleEQ1dEg2h+MO6Zs5nHatfyI7QrLp7KgKq0iEUYkCJWvAamJbjA67IsJ3N3psWfaluDrClImUMf8aZuIeECcn1jNoc5qDvfvBkMIVGeKJZnYkNfBBuM8hTAiP35hJMj909IFQK8ehCsHoVUy1fDW1uM38BP5X8xZQrppfiEpx+dVQAxu7nRsUOa8FZsxJEODx3akUzlWQpcg2zxFFv1B6/FAE+yWGO9gk4KKWfQj2ZsnomH8WMDKesy0Dx1zcTNP8+nVbtR8sgp0n0mHPRzT8hkzHqHBQZdvxV4pWAvZzsz3V/dLYyYulEn0/2roOv9ESzn29D8hOV9LvaKCsv3FXbjT/DVUs+PYjndanrZO60Jm6Ag4aF50UtnPd7cqaFdZoDIK+2IB/ufS75wFSnoj0OTXk2KejqDixaNdvU79acnKnq+XQDC/cmLeObxP8N92hQJNBu7ePPpdD6mYOAia6oTgwYiRB8aiHSgmVblCJ+h6n5lkm7Zz6v6jxixrNxaJ8BqvWHz2UPHMbO38LIqYl7clZbVSZOdmTSFdw/P9g69K3l3skRatYgwmWpT8OeK8BDLvJifBWARkR3dbaXtaLCIbkedvKgkj06qfzOK/hX7dHJk0k6HrfvuqaFHW+nwujapqtqsMdOwg+yPdV3l6EwWAfyjGstZut6R5VrG99V32D06FNrFhP4+jtNynJtzvuPG9bLXMzVdTCOoFJpbY3/d0PQJgS7IjElLy1WPYcEK5hTxmGKeUxdBzDKWxfF/XGV5drt8ubTthvnoVdyr7ygeesXE8o06W2FYpSw4yrG3ECncZ9lR4AqdHum7G7IBXLiiFKoM5iui7L9vsVNs1v/qc4TU9bqUxDlrrIPjwenWMPGyEN0Rgb+4lDYfMr9rNUuVIXqYjhyIH0ojv19Fi0JfFBHeJKSHaaBTXuqCXn25JALafF16JiqwkoEXx5j4fe59afOe5k2yuYXlanu1T8TLKSSSGDyFZEVYaffDUvK+lVRdkptiayfbXZQpM/ESCYD4JZjrek+aqrOVx6byVoL1yScGqfqDptdqQmxUnfpyIkbFXScjtYeu/ayIqmUC5mrkMQ2vNWIz/EdTtXj7fYA2/0hI8gbQedsxYsuOMdgtwpCL2JDHJVuw6CJ5CwdRZSU9gCKDX0B/5sUVJg71e+naxBsgnNyLi0P50I5OvX85rTP62DQ3gL3COypcmt7I4W77FM5cIRNkRXrUnj83smxdpJWXxW+53I3IZkU90U+lecDlgbffhml5Qb7ar2dPM/fei9Wra3gLeVeKOOPqcR/tBMMcrVRWv8maL7DULDG32jijl7AydOibGmHTC1XHS06z9+e1owKxPWmMP4mIXctlwuw5uuql5vHZiBJgebX3/mBfux5AYU48xVQHyMPJ3/aZ+ZUjnC7rGC7T7q9TbxsumhcoNi/nDh1TQ09BOcdUeh84iFTm0BVMqbz0hckb3rJiIIXw7ih44TTVfkSRG6hCoSqEaad4GBaTLKGrNKIIj7MpoIUTmRXBr2VspgiZztPin+rVCjvHpndR0i5MUn+M9liro7JQYiWHdG+PKhvgOr+jUuvEFe+sRv5Kj81zLxY5sl6owAv0epMVzFiFKrpSZijgt+4marnAraGIcvGz6DlPlTVNvoePCo73/tDGCCqaZp2yuN8oW2GgbNilRHKd9HyBcI4bE2HJRX4B4ucysiHpZmAmhzB35j0xTadZPq8zAO6wFMMJjhCGvEpJSwjMMaKkYAE9uy79o5P7so5E++hiBrgS8gMAOGP/bcAErFHh/MXTbSwD9Om6YOV2cfluCTQJknlnKY0hHwcgfAlkfi9VQio6iwUdgCc0zUFkVTdomJfn81EXnTMZ2HjpQz0HLNba+0BvBPZvym4Ac3yKff9wZJIBUexBckQl57XIfBY+MiykbZPmme+EUJSasVu1XfmpsAurpK6Z/VBDQHQDBXfcK5OhmyMkY8rTbLeKS1q7XTX1xzP0SJAaB+JSzA/UNLv7wJd4Cc+vN4oLT9LsONx1LyyJ+B9BIapfR29sN9ly8I+nxKAiHS2VuaCC2772Bb0i0x7gqMpbJOSkck7ZGQnISFp8TURhVh7+2Dzdv2xmEX/EtvIrWP9pNNYdSeVveFVWzyj1U9BXmRb4qozD29wqhzrkaGP9NCt+7QVRoMcDFDCTQAeA4r1bUdWqUmrItghqv7cYVXhQZfECgS9llwB4xzAWP37G2uokNThDAO3Yp71C+xcVHXRjbN3AS3VXkrm9dRCoRUEpy4pWU4TKK+IiFAxFtDBSq6AvtpJRxIIpzs3Lo8DK41iOCF1QAH9xeVx6DmpWnamtIoQ5hu2n/1ZacxdIMc6jfFdFlc6n94fpMRCnton6bhmC1cYhZZJVnIXS2WOKnCa7Tl6slQaH8t30oCxPyhfRPuYZTyK8H7e99ohAWHvH+axaXBaUXEp2Ef/dKaTf3bUUic8uxpnGKLbveJ4eX6ULWofwaSWFw7t10OzYOpFqafzP3vUzCfn8MNecCAeaS+EarTKqg4UzpOpkpmo960EJgO/LieO/om4/tARKxtx1syJhG9p7ReVVoXgZmYf61E2TwuS/nXMPPTbT6yyI0LHTI7HAAKOB6IUUMu2Sy1k/FI8kuggCG47sWj9aWTp5QlWtC1kINIqxPWqo6ewYswjk13ucmwV5Bi87M8omdn25Pba/VQp5eiB67avS/dE/e18I4GwvErYaPxE5i9FOuzgWAFNE61vgIkUxbgF0RavwNpov1CN02f4f1iLxBuGLE32lSQcog2zSjyaKuu3XUXS9L3EJfhI1Eme1tkEPfUwlkIwmen4CVGW6viDuQvD9nDuNMwUKqz77xI58mKy1SALnDZTiuTQHUVD1cp+az5kFHF4K+Oy0TpF5SJE8701s9IdsET0E1xJIlT3qYkIYplxJwaaoot2Uki7Xp4pSpqStJ0ZAIb136XuFOidGUViGydgm8xLoPmx/\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":"{\"path\":"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{},"partialJson":"{\"path\":"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".im"},"partialJson":"{\"path\":\".im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"XOfe0qcBg65oslwQ9Yfsz+TARJiOn6e46rZwDqrMsCnqUydY1m15gP1I0cxRRpV2Mt448UNcnLuDnZkY4R+DcHvUkIItDuE8eleEQ1dEg2h+MO6Zs5nHatfyI7QrLp7KgKq0iEUYkCJWvAamJbjA67IsJ3N3psWfaluDrClImUMf8aZuIeECcn1jNoc5qDvfvBkMIVGeKJZnYkNfBBuM8hTAiP35hJMj909IFQK8ehCsHoVUy1fDW1uM38BP5X8xZQrppfiEpx+dVQAxu7nRsUOa8FZsxJEODx3akUzlWQpcg2zxFFv1B6/FAE+yWGO9gk4KKWfQj2ZsnomH8WMDKesy0Dx1zcTNP8+nVbtR8sgp0n0mHPRzT8hkzHqHBQZdvxV4pWAvZzsz3V/dLYyYulEn0/2roOv9ESzn29D8hOV9LvaKCsv3FXbjT/DVUs+PYjndanrZO60Jm6Ag4aF50UtnPd7cqaFdZoDIK+2IB/ufS75wFSnoj0OTXk2KejqDixaNdvU79acnKnq+XQDC/cmLeObxP8N92hQJNBu7ePPpdD6mYOAia6oTgwYiRB8aiHSgmVblCJ+h6n5lkm7Zz6v6jxixrNxaJ8BqvWHz2UPHMbO38LIqYl7clZbVSZOdmTSFdw/P9g69K3l3skRatYgwmWpT8OeK8BDLvJifBWARkR3dbaXtaLCIbkedvKgkj06qfzOK/hX7dHJk0k6HrfvuqaFHW+nwujapqtqsMdOwg+yPdV3l6EwWAfyjGstZut6R5VrG99V32D06FNrFhP4+jtNynJtzvuPG9bLXMzVdTCOoFJpbY3/d0PQJgS7IjElLy1WPYcEK5hTxmGKeUxdBzDKWxfF/XGV5drt8ubTthvnoVdyr7ygeesXE8o06W2FYpSw4yrG3ECncZ9lR4AqdHum7G7IBXLiiFKoM5iui7L9vsVNs1v/qc4TU9bqUxDlrrIPjwenWMPGyEN0Rgb+4lDYfMr9rNUuVIXqYjhyIH0ojv19Fi0JfFBHeJKSHaaBTXuqCXn25JALafF16JiqwkoEXx5j4fe59afOe5k2yuYXlanu1T8TLKSSSGDyFZEVYaffDUvK+lVRdkptiayfbXZQpM/ESCYD4JZjrek+aqrOVx6byVoL1yScGqfqDptdqQmxUnfpyIkbFXScjtYeu/ayIqmUC5mrkMQ2vNWIz/EdTtXj7fYA2/0hI8gbQedsxYsuOMdgtwpCL2JDHJVuw6CJ5CwdRZSU9gCKDX0B/5sUVJg71e+naxBsgnNyLi0P50I5OvX85rTP62DQ3gL3COypcmt7I4W77FM5cIRNkRXrUnj83smxdpJWXxW+53I3IZkU90U+lecDlgbffhml5Qb7ar2dPM/fei9Wra3gLeVeKOOPqcR/tBMMcrVRWv8maL7DULDG32jijl7AydOibGmHTC1XHS06z9+e1owKxPWmMP4mIXctlwuw5uuql5vHZiBJgebX3/mBfux5AYU48xVQHyMPJ3/aZ+ZUjnC7rGC7T7q9TbxsumhcoNi/nDh1TQ09BOcdUeh84iFTm0BVMqbz0hckb3rJiIIXw7ih44TTVfkSRG6hCoSqEaad4GBaTLKGrNKIIj7MpoIUTmRXBr2VspgiZztPin+rVCjvHpndR0i5MUn+M9liro7JQYiWHdG+PKhvgOr+jUuvEFe+sRv5Kj81zLxY5sl6owAv0epMVzFiFKrpSZijgt+4marnAraGIcvGz6DlPlTVNvoePCo73/tDGCCqaZp2yuN8oW2GgbNilRHKd9HyBcI4bE2HJRX4B4ucysiHpZmAmhzB35j0xTadZPq8zAO6wFMMJjhCGvEpJSwjMMaKkYAE9uy79o5P7so5E++hiBrgS8gMAOGP/bcAErFHh/MXTbSwD9Om6YOV2cfluCTQJknlnKY0hHwcgfAlkfi9VQio6iwUdgCc0zUFkVTdomJfn81EXnTMZ2HjpQz0HLNba+0BvBPZvym4Ac3yKff9wZJIBUexBckQl57XIfBY+MiykbZPmme+EUJSasVu1XfmpsAurpK6Z/VBDQHQDBXfcK5OhmyMkY8rTbLeKS1q7XTX1xzP0SJAaB+JSzA/UNLv7wJd4Cc+vN4oLT9LsONx1LyyJ+B9BIapfR29sN9ly8I+nxKAiHS2VuaCC2772Bb0i0x7gqMpbJOSkck7ZGQnISFp8TURhVh7+2Dzdv2xmEX/EtvIrWP9pNNYdSeVveFVWzyj1U9BXmRb4qozD29wqhzrkaGP9NCt+7QVRoMcDFDCTQAeA4r1bUdWqUmrItghqv7cYVXhQZfECgS9llwB4xzAWP37G2uokNThDAO3Yp71C+xcVHXRjbN3AS3VXkrm9dRCoRUEpy4pWU4TKK+IiFAxFtDBSq6AvtpJRxIIpzs3Lo8DK41iOCF1QAH9xeVx6DmpWnamtIoQ5hu2n/1ZacxdIMc6jfFdFlc6n94fpMRCnton6bhmC1cYhZZJVnIXS2WOKnCa7Tl6slQaH8t30oCxPyhfRPuYZTyK8H7e99ohAWHvH+axaXBaUXEp2Ef/dKaTf3bUUic8uxpnGKLbveJ4eX6ULWofwaSWFw7t10OzYOpFqafzP3vUzCfn8MNecCAeaS+EarTKqg4UzpOpkpmo960EJgO/LieO/om4/tARKxtx1syJhG9p7ReVVoXgZmYf61E2TwuS/nXMPPTbT6yyI0LHTI7HAAKOB6IUUMu2Sy1k/FI8kuggCG47sWj9aWTp5QlWtC1kINIqxPWqo6ewYswjk13ucmwV5Bi87M8omdn25Pba/VQp5eiB67avS/dE/e18I4GwvErYaPxE5i9FOuzgWAFNE61vgIkUxbgF0RavwNpov1CN02f4f1iLxBuGLE32lSQcog2zSjyaKuu3XUXS9L3EJfhI1Eme1tkEPfUwlkIwmen4CVGW6viDuQvD9nDuNMwUKqz77xI58mKy1SALnDZTiuTQHUVD1cp+az5kFHF4K+Oy0TpF5SJE8701s9IdsET0E1xJIlT3qYkIYplxJwaaoot2Uki7Xp4pSpqStJ0ZAIb136XuFOidGUViGydgm8xLoPmx/\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".im"},"partialJson":"{\"path\":\".im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".im"},"partialJson":"{\"path\":\".im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".im"},"partialJson":"{\"path\":\".im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impe"},"partialJson":"{\"path\":\".impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"XOfe0qcBg65oslwQ9Yfsz+TARJiOn6e46rZwDqrMsCnqUydY1m15gP1I0cxRRpV2Mt448UNcnLuDnZkY4R+DcHvUkIItDuE8eleEQ1dEg2h+MO6Zs5nHatfyI7QrLp7KgKq0iEUYkCJWvAamJbjA67IsJ3N3psWfaluDrClImUMf8aZuIeECcn1jNoc5qDvfvBkMIVGeKJZnYkNfBBuM8hTAiP35hJMj909IFQK8ehCsHoVUy1fDW1uM38BP5X8xZQrppfiEpx+dVQAxu7nRsUOa8FZsxJEODx3akUzlWQpcg2zxFFv1B6/FAE+yWGO9gk4KKWfQj2ZsnomH8WMDKesy0Dx1zcTNP8+nVbtR8sgp0n0mHPRzT8hkzHqHBQZdvxV4pWAvZzsz3V/dLYyYulEn0/2roOv9ESzn29D8hOV9LvaKCsv3FXbjT/DVUs+PYjndanrZO60Jm6Ag4aF50UtnPd7cqaFdZoDIK+2IB/ufS75wFSnoj0OTXk2KejqDixaNdvU79acnKnq+XQDC/cmLeObxP8N92hQJNBu7ePPpdD6mYOAia6oTgwYiRB8aiHSgmVblCJ+h6n5lkm7Zz6v6jxixrNxaJ8BqvWHz2UPHMbO38LIqYl7clZbVSZOdmTSFdw/P9g69K3l3skRatYgwmWpT8OeK8BDLvJifBWARkR3dbaXtaLCIbkedvKgkj06qfzOK/hX7dHJk0k6HrfvuqaFHW+nwujapqtqsMdOwg+yPdV3l6EwWAfyjGstZut6R5VrG99V32D06FNrFhP4+jtNynJtzvuPG9bLXMzVdTCOoFJpbY3/d0PQJgS7IjElLy1WPYcEK5hTxmGKeUxdBzDKWxfF/XGV5drt8ubTthvnoVdyr7ygeesXE8o06W2FYpSw4yrG3ECncZ9lR4AqdHum7G7IBXLiiFKoM5iui7L9vsVNs1v/qc4TU9bqUxDlrrIPjwenWMPGyEN0Rgb+4lDYfMr9rNUuVIXqYjhyIH0ojv19Fi0JfFBHeJKSHaaBTXuqCXn25JALafF16JiqwkoEXx5j4fe59afOe5k2yuYXlanu1T8TLKSSSGDyFZEVYaffDUvK+lVRdkptiayfbXZQpM/ESCYD4JZjrek+aqrOVx6byVoL1yScGqfqDptdqQmxUnfpyIkbFXScjtYeu/ayIqmUC5mrkMQ2vNWIz/EdTtXj7fYA2/0hI8gbQedsxYsuOMdgtwpCL2JDHJVuw6CJ5CwdRZSU9gCKDX0B/5sUVJg71e+naxBsgnNyLi0P50I5OvX85rTP62DQ3gL3COypcmt7I4W77FM5cIRNkRXrUnj83smxdpJWXxW+53I3IZkU90U+lecDlgbffhml5Qb7ar2dPM/fei9Wra3gLeVeKOOPqcR/tBMMcrVRWv8maL7DULDG32jijl7AydOibGmHTC1XHS06z9+e1owKxPWmMP4mIXctlwuw5uuql5vHZiBJgebX3/mBfux5AYU48xVQHyMPJ3/aZ+ZUjnC7rGC7T7q9TbxsumhcoNi/nDh1TQ09BOcdUeh84iFTm0BVMqbz0hckb3rJiIIXw7ih44TTVfkSRG6hCoSqEaad4GBaTLKGrNKIIj7MpoIUTmRXBr2VspgiZztPin+rVCjvHpndR0i5MUn+M9liro7JQYiWHdG+PKhvgOr+jUuvEFe+sRv5Kj81zLxY5sl6owAv0epMVzFiFKrpSZijgt+4marnAraGIcvGz6DlPlTVNvoePCo73/tDGCCqaZp2yuN8oW2GgbNilRHKd9HyBcI4bE2HJRX4B4ucysiHpZmAmhzB35j0xTadZPq8zAO6wFMMJjhCGvEpJSwjMMaKkYAE9uy79o5P7so5E++hiBrgS8gMAOGP/bcAErFHh/MXTbSwD9Om6YOV2cfluCTQJknlnKY0hHwcgfAlkfi9VQio6iwUdgCc0zUFkVTdomJfn81EXnTMZ2HjpQz0HLNba+0BvBPZvym4Ac3yKff9wZJIBUexBckQl57XIfBY+MiykbZPmme+EUJSasVu1XfmpsAurpK6Z/VBDQHQDBXfcK5OhmyMkY8rTbLeKS1q7XTX1xzP0SJAaB+JSzA/UNLv7wJd4Cc+vN4oLT9LsONx1LyyJ+B9BIapfR29sN9ly8I+nxKAiHS2VuaCC2772Bb0i0x7gqMpbJOSkck7ZGQnISFp8TURhVh7+2Dzdv2xmEX/EtvIrWP9pNNYdSeVveFVWzyj1U9BXmRb4qozD29wqhzrkaGP9NCt+7QVRoMcDFDCTQAeA4r1bUdWqUmrItghqv7cYVXhQZfECgS9llwB4xzAWP37G2uokNThDAO3Yp71C+xcVHXRjbN3AS3VXkrm9dRCoRUEpy4pWU4TKK+IiFAxFtDBSq6AvtpJRxIIpzs3Lo8DK41iOCF1QAH9xeVx6DmpWnamtIoQ5hu2n/1ZacxdIMc6jfFdFlc6n94fpMRCnton6bhmC1cYhZZJVnIXS2WOKnCa7Tl6slQaH8t30oCxPyhfRPuYZTyK8H7e99ohAWHvH+axaXBaUXEp2Ef/dKaTf3bUUic8uxpnGKLbveJ4eX6ULWofwaSWFw7t10OzYOpFqafzP3vUzCfn8MNecCAeaS+EarTKqg4UzpOpkpmo960EJgO/LieO/om4/tARKxtx1syJhG9p7ReVVoXgZmYf61E2TwuS/nXMPPTbT6yyI0LHTI7HAAKOB6IUUMu2Sy1k/FI8kuggCG47sWj9aWTp5QlWtC1kINIqxPWqo6ewYswjk13ucmwV5Bi87M8omdn25Pba/VQp5eiB67avS/dE/e18I4GwvErYaPxE5i9FOuzgWAFNE61vgIkUxbgF0RavwNpov1CN02f4f1iLxBuGLE32lSQcog2zSjyaKuu3XUXS9L3EJfhI1Eme1tkEPfUwlkIwmen4CVGW6viDuQvD9nDuNMwUKqz77xI58mKy1SALnDZTiuTQHUVD1cp+az5kFHF4K+Oy0TpF5SJE8701s9IdsET0E1xJIlT3qYkIYplxJwaaoot2Uki7Xp4pSpqStJ0ZAIb136XuFOidGUViGydgm8xLoPmx/\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impe"},"partialJson":"{\"path\":\".impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impecc"},"partialJson":"{\"path\":\".impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impecc"},"partialJson":"{\"path\":\".impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable"},"partialJson":"{\"path\":\".impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable"},"partialJson":"{\"path\":\".impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":".md","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":1,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":1,"toolCall":{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|P7wyxDz6dZPR26PXJvWLGeR37/bVs5C0/PviD6pL7HbTC6x1nJbdjMjCRvotswTAnsGqEPZHTGfPma19CRec4K9DaZIsirBn8h9Bq/t/eb2AOSh6r80e/5XXDZsHksV6jT4Wnpwno6JTKvAHgZqqFh5J5zpSb/vEpMfbpRr6xHuQEhMgfEmTUje4vsw4RkXzr6Sopgn9ETMJbmEzGmfbqfwch9ctd2+MehPBoYygmn2BmkvTpYiDJR2JjT8YsFXvfrmE5nVXVdY6PEHJFis1hBx1riOZheClchaEjvY0WEHx9nlLOwJX76x2ce0GHk3JxQnaCgRO3UIGQkvKT+5cqmqYxsky4JLiZJo8p1f2L62Z4SP1f1h1u1f3fUTzq8R35Ku3/jdfa5/lYq7Zl4QdZi0A5TwRsuo=","name":"read","arguments":{"path":".impeccable.md"}},"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941622783,"responseId":"dfHyTYlqvj1FOnNc4gGXAI5FFlxIH6vTy5uroYZvUvQD0pXJA+btoOqqlsQIW701mxYxO0Sm20v0GRxTKSd2rKTPcSVG30S7W28KGpDXUiFt33fRcfk8g8DV6rTpWexIIfExVqpgey8tAKNLJiwvAjiYWa3PPrThAh2Y8hKkHMWArpmbzljJZuFLF/GqO1MRsD0Q5wNvQsE7ohkTUlm5CIT4JPLINqLT8VG+qW0i75ygso3TkFbwbuk/ZJ2XHAZ0N6Vnyhr33OcxwhYa30ySawWDq9EZEB5CQCzC1/uBEJA0xAbiEUGOsqf+U9/rQI5VIxhIfEVjX+5h9XIVk6ctJLpX0VlVrzKkJBJsT+MmMC6zQMtg7VEBMRFszioU+yziiOsAMN8R8SPQoe+G+W82sntieeTtifMhCA=="}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"XOfe0qcBg65oslwQ9Yfsz+TARJiOn6e46rZwDqrMsCnqUydY1m15gP1I0cxRRpV2Mt448UNcnLuDnZkY4R+DcHvUkIItDuE8eleEQ1dEg2h+MO6Zs5nHatfyI7QrLp7KgKq0iEUYkCJWvAamJbjA67IsJ3N3psWfaluDrClImUMf8aZuIeECcn1jNoc5qDvfvBkMIVGeKJZnYkNfBBuM8hTAiP35hJMj909IFQK8ehCsHoVUy1fDW1uM38BP5X8xZQrppfiEpx+dVQAxu7nRsUOa8FZsxJEODx3akUzlWQpcg2zxFFv1B6/FAE+yWGO9gk4KKWfQj2ZsnomH8WMDKesy0Dx1zcTNP8+nVbtR8sgp0n0mHPRzT8hkzHqHBQZdvxV4pWAvZzsz3V/dLYyYulEn0/2roOv9ESzn29D8hOV9LvaKCsv3FXbjT/DVUs+PYjndanrZO60Jm6Ag4aF50UtnPd7cqaFdZoDIK+2IB/ufS75wFSnoj0OTXk2KejqDixaNdvU79acnKnq+XQDC/cmLeObxP8N92hQJNBu7ePPpdD6mYOAia6oTgwYiRB8aiHSgmVblCJ+h6n5lkm7Zz6v6jxixrNxaJ8BqvWHz2UPHMbO38LIqYl7clZbVSZOdmTSFdw/P9g69K3l3skRatYgwmWpT8OeK8BDLvJifBWARkR3dbaXtaLCIbkedvKgkj06qfzOK/hX7dHJk0k6HrfvuqaFHW+nwujapqtqsMdOwg+yPdV3l6EwWAfyjGstZut6R5VrG99V32D06FNrFhP4+jtNynJtzvuPG9bLXMzVdTCOoFJpbY3/d0PQJgS7IjElLy1WPYcEK5hTxmGKeUxdBzDKWxfF/XGV5drt8ubTthvnoVdyr7ygeesXE8o06W2FYpSw4yrG3ECncZ9lR4AqdHum7G7IBXLiiFKoM5iui7L9vsVNs1v/qc4TU9bqUxDlrrIPjwenWMPGyEN0Rgb+4lDYfMr9rNUuVIXqYjhyIH0ojv19Fi0JfFBHeJKSHaaBTXuqCXn25JALafF16JiqwkoEXx5j4fe59afOe5k2yuYXlanu1T8TLKSSSGDyFZEVYaffDUvK+lVRdkptiayfbXZQpM/ESCYD4JZjrek+aqrOVx6byVoL1yScGqfqDptdqQmxUnfpyIkbFXScjtYeu/ayIqmUC5mrkMQ2vNWIz/EdTtXj7fYA2/0hI8gbQedsxYsuOMdgtwpCL2JDHJVuw6CJ5CwdRZSU9gCKDX0B/5sUVJg71e+naxBsgnNyLi0P50I5OvX85rTP62DQ3gL3COypcmt7I4W77FM5cIRNkRXrUnj83smxdpJWXxW+53I3IZkU90U+lecDlgbffhml5Qb7ar2dPM/fei9Wra3gLeVeKOOPqcR/tBMMcrVRWv8maL7DULDG32jijl7AydOibGmHTC1XHS06z9+e1owKxPWmMP4mIXctlwuw5uuql5vHZiBJgebX3/mBfux5AYU48xVQHyMPJ3/aZ+ZUjnC7rGC7T7q9TbxsumhcoNi/nDh1TQ09BOcdUeh84iFTm0BVMqbz0hckb3rJiIIXw7ih44TTVfkSRG6hCoSqEaad4GBaTLKGrNKIIj7MpoIUTmRXBr2VspgiZztPin+rVCjvHpndR0i5MUn+M9liro7JQYiWHdG+PKhvgOr+jUuvEFe+sRv5Kj81zLxY5sl6owAv0epMVzFiFKrpSZijgt+4marnAraGIcvGz6DlPlTVNvoePCo73/tDGCCqaZp2yuN8oW2GgbNilRHKd9HyBcI4bE2HJRX4B4ucysiHpZmAmhzB35j0xTadZPq8zAO6wFMMJjhCGvEpJSwjMMaKkYAE9uy79o5P7so5E++hiBrgS8gMAOGP/bcAErFHh/MXTbSwD9Om6YOV2cfluCTQJknlnKY0hHwcgfAlkfi9VQio6iwUdgCc0zUFkVTdomJfn81EXnTMZ2HjpQz0HLNba+0BvBPZvym4Ac3yKff9wZJIBUexBckQl57XIfBY+MiykbZPmme+EUJSasVu1XfmpsAurpK6Z/VBDQHQDBXfcK5OhmyMkY8rTbLeKS1q7XTX1xzP0SJAaB+JSzA/UNLv7wJd4Cc+vN4oLT9LsONx1LyyJ+B9BIapfR29sN9ly8I+nxKAiHS2VuaCC2772Bb0i0x7gqMpbJOSkck7ZGQnISFp8TURhVh7+2Dzdv2xmEX/EtvIrWP9pNNYdSeVveFVWzyj1U9BXmRb4qozD29wqhzrkaGP9NCt+7QVRoMcDFDCTQAeA4r1bUdWqUmrItghqv7cYVXhQZfECgS9llwB4xzAWP37G2uokNThDAO3Yp71C+xcVHXRjbN3AS3VXkrm9dRCoRUEpy4pWU4TKK+IiFAxFtDBSq6AvtpJRxIIpzs3Lo8DK41iOCF1QAH9xeVx6DmpWnamtIoQ5hu2n/1ZacxdIMc6jfFdFlc6n94fpMRCnton6bhmC1cYhZZJVnIXS2WOKnCa7Tl6slQaH8t30oCxPyhfRPuYZTyK8H7e99ohAWHvH+axaXBaUXEp2Ef/dKaTf3bUUic8uxpnGKLbveJ4eX6ULWofwaSWFw7t10OzYOpFqafzP3vUzCfn8MNecCAeaS+EarTKqg4UzpOpkpmo960EJgO/LieO/om4/tARKxtx1syJhG9p7ReVVoXgZmYf61E2TwuS/nXMPPTbT6yyI0LHTI7HAAKOB6IUUMu2Sy1k/FI8kuggCG47sWj9aWTp5QlWtC1kINIqxPWqo6ewYswjk13ucmwV5Bi87M8omdn25Pba/VQp5eiB67avS/dE/e18I4GwvErYaPxE5i9FOuzgWAFNE61vgIkUxbgF0RavwNpov1CN02f4f1iLxBuGLE32lSQcog2zSjyaKuu3XUXS9L3EJfhI1Eme1tkEPfUwlkIwmen4CVGW6viDuQvD9nDuNMwUKqz77xI58mKy1SALnDZTiuTQHUVD1cp+az5kFHF4K+Oy0TpF5SJE8701s9IdsET0E1xJIlT3qYkIYplxJwaaoot2Uki7Xp4pSpqStJ0ZAIb136XuFOidGUViGydgm8xLoPmx/\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":2925,"output":223,"cacheRead":2432,"cacheWrite":0,"totalTokens":5580,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941622783,"responseId":"oQqNWWOkCxhoIjbseRwz8DTrMD+V3llJ2p8/FiOQbONl9Url3WMlQ3o8pv38AAqbe/HOKnSPDysoFYY0LIFoEAZG6t+bYdaA4UAgfW+yo75c9I1uOfrOGyYkcPV+qg8mWy+/HIK8wMq5H31dXWjPMs9S6iFg0inXsT5jUa/vWKEO1m7JoRjNRwphqkLrdHzI5kwGsaEDUjFHrpRVy8N4Q3Ig1HrexoGMOnL7M8Obr5ldTttwbcBK2TGc4joHM6iWxWt6CU2eirx+0eK2LNNHIferm2vNuJqM3SERT2hNfBJ+iaRpZM+HbHsBwsAtv8MiXWqVCqnqZaWRRlkbsqD0iEAwUlmdgfj4cOwixFnAMdmoKgpO2gqNXayJpxM9zEv9VQBu1TckL+cmR5q5Vy5lp6QZP9s6FgtlCw=="}}
{"type":"tool_execution_start","toolCallId":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","toolName":"read","args":{"path":".impeccable.md"}}
{"type":"tool_execution_end","toolCallId":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","toolName":"read","result":{"content":[{"type":"text","text":"ENOENT: no such file or directory, access '/home/alex/.pi/agent/skills/frontend/.impeccable.md'"}],"details":{}},"isError":true}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","toolName":"read","content":[{"type":"text","text":"ENOENT: no such file or directory, access '/home/alex/.pi/agent/skills/frontend/.impeccable.md'"}],"details":{},"isError":true,"timestamp":1775941631009}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","toolName":"read","content":[{"type":"text","text":"ENOENT: no such file or directory, access '/home/alex/.pi/agent/skills/frontend/.impeccable.md'"}],"details":{},"isError":true,"timestamp":1775941631009}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":2925,"output":223,"cacheRead":2432,"cacheWrite":0,"totalTokens":5580,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941622783,"responseId":"oQqNWWOkCxhoIjbseRwz8DTrMD+V3llJ2p8/FiOQbONl9Url3WMlQ3o8pv38AAqbe/HOKnSPDysoFYY0LIFoEAZG6t+bYdaA4UAgfW+yo75c9I1uOfrOGyYkcPV+qg8mWy+/HIK8wMq5H31dXWjPMs9S6iFg0inXsT5jUa/vWKEO1m7JoRjNRwphqkLrdHzI5kwGsaEDUjFHrpRVy8N4Q3Ig1HrexoGMOnL7M8Obr5ldTttwbcBK2TGc4joHM6iWxWt6CU2eirx+0eK2LNNHIferm2vNuJqM3SERT2hNfBJ+iaRpZM+HbHsBwsAtv8MiXWqVCqnqZaWRRlkbsqD0iEAwUlmdgfj4cOwixFnAMdmoKgpO2gqNXayJpxM9zEv9VQBu1TckL+cmR5q5Vy5lp6QZP9s6FgtlCw=="},"toolResults":[{"role":"toolResult","toolCallId":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","toolName":"read","content":[{"type":"text","text":"ENOENT: no such file or directory, access '/home/alex/.pi/agent/skills/frontend/.impeccable.md'"}],"details":{},"isError":true,"timestamp":1775941631009}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**Planning","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Skill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Execution","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**\n\nI","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" need","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" remember","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" always","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" \"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\"","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" in","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Skills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" list","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" The","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" user","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" clarified","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" they","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" want","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" use","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" question","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" tool","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" for","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" decisions","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" but","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" their","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" specific","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" request","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" doesn","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"’t","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" need","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" further","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" clarification","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" also","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" need","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" check","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" SK","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ILL","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".md","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" if","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" is","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" necessary","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" should","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" run","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" since","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it's","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" missing","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" context","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" After","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. After"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. After"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ward","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I'll","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" followed","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" by","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"on","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'on"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'on"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"board","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" ensure","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" include","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"del","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'del"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'del"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pol","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'pol"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'pol"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" as","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" user","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" explicitly","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" requested","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" those","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" features","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\n\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**Determ","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determ"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determ"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ining","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Skill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**\n\nI","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"’m","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" adding","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" both","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" skills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" since","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" user","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" specifically","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" requested","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" characteristics","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" matched","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" by","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" them","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" The","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" plan","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" is","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" set","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" with","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" followed","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" by","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" The","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"M","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'M"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'M"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"UST","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" DO","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" guidelines","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" say","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" that","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" should","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" always","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" skill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" but","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it's","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" not","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" necessarily","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" However","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" must","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" come","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" before","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" other","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" skills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" if","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"’s","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" required","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" So","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I'll","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" ensure","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" loads","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" followed","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" by","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" then","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" include","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" at","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" an","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" appropriate","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" time","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\n\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**Dec","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Dec"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Dec"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"iding","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Skill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Loading","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**\n\nWhile","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it's","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" not","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" mandatory","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" put","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it's","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" wiser","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" because","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" .","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the ."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the ."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".md","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" is","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" missing","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" After","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" that","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" loading","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" should","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" go","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" followed","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" by","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"on","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'on"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'on"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"board","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"del","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'del"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'del"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pol","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'pol"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'pol"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Since","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" is","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" a","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" meta","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-s","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-s"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-s"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"kill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" might","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" include","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" at","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" start","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" or","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" end","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" as","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" guidelines","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" say","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" always","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" but","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" don","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"’t","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" specify","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" its","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" position","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" So","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" should","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" be","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\n\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**Organ","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organ"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organ"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"izing","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Skill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Load","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Sequence","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**\n\nI","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" need","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" make","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" sure","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" all","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" appropriate","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" skills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" are","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" loaded","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Since","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" is","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" a","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" general","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" skill","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" might","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" include","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" it","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" at","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" front","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" However","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" SK","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SK"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SK"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ILL","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Router","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" suggests","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" sequence","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" should","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" start","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" with","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" followed","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" by","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" so","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" on","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Including","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" '","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including '"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"c","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'c"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"av","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"'","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman'"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" doesn","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"’t","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" seem","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" conflict","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" with","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" guidelines","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" For","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" clarity","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" I","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" could","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" outline","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" as","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" then","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" overall","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\n\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**Craft","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Craft"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Craft"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ing","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Skills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Output","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**\n\nSkills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"  \nOrder","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"  \nWhy","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"seed","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" context","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"visual","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" system","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-run","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" flows","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"person","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (person"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (person"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ality","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"finish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"brief","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-mode","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":")","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\n\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**Construct","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Construct"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Construct"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ing","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Final","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" Response","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"**\n\nSkills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"  \nOrder","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"  \nWhy","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"se","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (se"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (se"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eds","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" context","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"sets","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" visual","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" direction","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"build","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (build"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (build"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"s","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-run","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" flow","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"adds","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" personality","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" to","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" avoid","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" generic","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" AI","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" UI","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"provid","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provid"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provid"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"es","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" final","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" fit","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-and","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"-f","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-f"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-f"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"inish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish),"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman ("}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ens","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ens"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ens"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"ures","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" concise","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":" mode","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":").","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode)."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode)."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_delta","contentIndex":0,"delta":"\n\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\n\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"thinking_end","contentIndex":0,"content":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_start","contentIndex":1,"partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":""}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"Skills","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":",","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight,"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"Order","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" →","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight →"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"\n","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\n"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"Why","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":":","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy:"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" teach","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-im","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-im"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"pe","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impe"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"cc","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impecc"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"able","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" seeds","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" missing","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" context","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":";","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-design","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" defines","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" distinctive","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" visual","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" direction","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":";","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" onboard","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" builds","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" the","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" first","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-run","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" flow","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":";","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" delight","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" inject","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight inject"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight inject"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"s","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" non","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"-g","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-g"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-g"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"eneric","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" personality","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":";","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" polish","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" finishes","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" details","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":";","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details;"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" cav","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; cav"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":"eman","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" =","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman ="}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman ="}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" brief","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":" mode","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":1,"delta":".","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"TFAQStQt1J80VQ55BU2vJXimCmTr4Mq67+aOqbn4YEB4McIx+yFwqG1VeHmv9EBygofQxYje3SjMLDOh/+RoDm1IRf6JzeYOkHD6jzx+X/6d9ox9cCxWe2KkaSB9YC2gszzALvyZA8B4WLbaznA7o1RHSeUODhksvFwEAxprwdjiDICMYhoReyGA9AWBBwVC1SVVO0SkD/nVe/w5LwtFRnXLsJ8kIDR74L7+CStekHbpYT8sZWJSo+2z3bmBz/k98JTYt6ck+nUYVMcAI22YYFBt+TjMCOR2iAvKYaBnXOiWfW9idm1bKDed1AilFPpSeD0xekon4fG1hx9I6NbRn67Q5KdSsAdfAT18R73yHGMfhs0tclV1b6DvMT/o7Au1dBqQBHiivecJKZyURLBplCYBv7qvhtVLZ1lRlXuB3s2gN6SPS+00ymu271mScnE3F43Na0c9kEmiBN4FmKArmord2sLhPolB7ekR8Lo67IgQR8xJgTCCx0I6P8kd8b4j08OnxgBeBNgbuCU/0PcB5w8jfEbPwRMDvubKE4AbpAJtl8Cx7NWgU+HNeBX+X8ztWmGlC83TzS0SP7rcAu+Blz7zcVz6OgK7/5VSCDmn0WptvqcITDncmH4+xtsAaaF1Sd9mdjYADQf6otIyasO2BS6vt1XJ9qeTMRGwJkk62qT4r2fiMA3TBeaRxxssOyMA9t1AqIg11a5lQOddyIEW3XJALNBersiSp+P/Rdk5aDxXLxK/gmtiYHauNRFszOmyk9jwIAJLSjBJh2JVDdqEdF68CBAqJ6SlOZX5qjsq23RYNGkSZglTEAXmM/D9VyE4/TJumJCUz1w5s5ieAuwhXijfGWvo9BGltCHoEemBSUHZOSKw+vsgSV52JlaE5D3hZBpYTY0MszpCqAnvcj4mYI3wHHCoY1clAzWeMx0Mb4lvCUUl3xMY9uNjJ0TDLU1Py8vpZeIl6iD+k5aSI+hBe0IRuHvy3NF5Jz+ehsv9ICTNe7NbtcCWuu4qjvJnmIKXGD3egQuvQGieEJP2ndfJtKGF7fKTQB+6ATze2uD4rp+PEP4TU1O5mX042HVbLI7tQZ81/5sUaiN1Oruppu7FD/jiUrxmYG+jTDc6e+jfn5sxam4pmWCqrcRmVruXCWnqHn/3tLGAsBxkAi9IaX6DjJ0fAGMWzPUq1Bc+DuKcnDAB1+b5osf0TOQrEh54BYY4Of3b8Tz+K6m1U3+hvFSJh0YgzdX0OM2g3rPAYNowLL00yxhktTGRgtn09QgecgEvnShwJW0X3xVv3S4WEDMJDz8BUY0vDg5gLyRx8bPYYIqQmrjArun1IN49mcRA5lSNBrz0h6WU9Z6+KSG+rs8PWV+nQhZw16y+Flj+FZfqoPi7Nm7VnrSDbvLEYu/HR6urMgUiNEV8N1+/AlH48hJ0q9ZGCCLxbNcnDbXBTNr3DCzhQgU28lAHmfs+FcnIqK1ok4e2pFJdePdisvv125kiImWUM906IjcXhqPQTDcwCwaGqqd+p89LOlacsBB8iQVccw0uCnDbjw8M3kTBratsa6GRKWRmae174s+/GHNL0ODK5XEdyVm+0QdUBO09Yff9bv8Ml46TMIXzr4AwbVfLJO8iTQkpcI4YmPbLA04yj9SaUPCxk2GPmAyuwag6tlgj/7YgWW7v+uZfF8+8PaUyPbCjuzwmI8u2SZwtMA1c2eyf7com4bEPwB4K5/7ggRHwomivYatJZrqV7HTmvMDCSQEbB+McuD02HlPZyKuEF/w6veII2tunFVbwfY5eCU1j8GkPzPzcmIt2zAQEvenPm7Aeev/JLfNv7ZgTabjlxKzdGe2ctUDLLbNI32VrqYtBZrQ2P7T7WTnfYj0WtjBWsk1J29CF7u7QSAUuNWPbM9MXG3JpHU0CLmU4agfAHiN8Qo2cyO/hWPbTtODxpJU1y1wPFDLkHvnLTpSM2uSH7xy6o97S8el5MLHPTPXHaU17/q8iuL32/vQ4wpo7x5+ItT/4Tl/fFcsmTZUlAZYhjUj48bV7CsUK40Myg6XEPwfUlCTRd8HVS/RHrRuKcDzFagm6oEwvuOpQRY1K8bA8Mm2sxhyFXf5REMtoXudVY6ZVO9tWPiMZ+Qe2UETcGjW1gIzlbMDyg4BE+UROnn8yDNmYq/OuRQDYNEoJDgQ8jjCY+WCnvtHxsa3pFXSZWLJoPM/eH92W0MDqzPa9dMAUbzauGfBWwg0sT+NktI87VFxciKpB6FWc7FzclL3ijYOUXceyNOSf8psMeVwWzlYAF7DNvuM56I5xkR9wUlsORSRgHeDsBOUrTlgJSiGd61g82nGPfuvQAS3QaRuSd6DE51ZUXvgeQmPDlSOtLEKOmNHJzhTs+Ij50WhhLUx1pbYBDOlj2VNEXPIZ9LLERrIpueMFONtCD6uIg25ZH50b+W9j7iFDbUNqLL20Dcu0aRRz6LSNzNicpZ3MHMHv4jy0uVaZqo9a7LfUkluafyXGRxqJj9vhcxuQkAmQrlzNICus8JqGGxZ3rL/xfk5hUmmPLBCYZZXhMzBmR4mRuhV3iGm3fFb+8GcWWc7LbtdXXht8mMQCOkiRU40RdQxvi/ZGWX/Y6y3o7kvvjTbX8lJ9cpT9EUywb9C0/4aMlRegi2q7P2UMRDJRc+uD3Uj7rEBFhlGjzSHqvWzdH7oiOwLWqp54Z4IO788vvvvGQfhXi4IK04Z+IOX80yNAWWxdkv+dAbh+lGQCMrzoGmpzpI+dMP0ZokLSOuXq3EETTH02Xb4ATKTJkA8hL06Q1tXINqC/4OX4rS7ZAHdELJWwPPoOazmVC5mCF1uuec1EkpudT38RMn57/j3LqRxPBggV7GhtyKM06MPRnB2J+eT9T0aYmZjRz6xpd+6QMUwcjtnAU8WG2tXQy1AaK7ydtmLqXfdcqpZYjChbKad6FcJM3Oto4TXySNTUGA/ZvXF1F3J3ABOIiNrz2DzTVd457hkq/7u1etNGzeqicXcVl/kI+l2fokOtfGdKb0zcQMJ7dhqP+AEpgGhJS0mNI2asIUF5tEv8BreRIt1qCzMJrlBK9obzksTou9hqFAGCDNRmTndMw9hlYOaInm4FI+y4RsCrPzoauogve8Xle0/aEPAtr4cR7+LIfjIO46+YK5tXvPbzWADAgqcK3ILtyvsw0iTFLPIBmnV88XuJf5uZ/r1lWJUl005cA+92NAmV0GOP80G2qhfBFjnUFyN1V6byUxNNDSqWBfJxTnbDy6jGPDDBLHqvBAYD7GOCd3zjr6xFWPehDRB6PWZ90aJkyepPK4kNMPbyxbCHBJS+JH54Sb4gbhwiDn82vMCSphYziwY5idOuGA4UIXpLvQJ7njB9CZyF+SW6g3fR+JIfOV3S6rFiwJRkLpJBlx6FlMbbNQy9S1p5eI+12PlL8k4vl0OjJcKmz7qfILXziw7rTFIFGJHH0AfXPgk82bm8XgqYdXCxxFSeqsmZ8AD0bZMNF/BeeiRTnLfTEw3VE0hhZIY/EikRkh1Y2UeR+EthNrQJRenveblQaTrVWfk8RKo/FLEQDwP0P2kBqoDl2zvRHGvsr2Quw8SnR/V7Ef8VYY0VBrVsdmmrnbTPxeoZys+2OmYIrj2IgCItHnOOQRWpxZeDBr6n7SQbtdszAkuA20AIwamlwYZIfDrPDFFj7ssdHJZlHrFHIt7VMnowVQb4pSPAM1GQ9KMrEOaRXqlNBxXsJ0kIlYVdhfMXvRXxHr32G8Cdablh69TEnHM3BU3jSy3R7GcDY+Cx5Z5XjiMCRwMkxswjmfwKMkhW5m+kFOaDmy4OHcIBJWp2n12RW3beg6b7Exc/eFRSg1e/hC5fA8Ig3ygx5KPgfogXb7BD6HfQypf53HUneaNUWl30VNBwYGbZuAVRB8lS3wgbz/vbJjLx0h/nuMRn2uQ9xY6nxGaluXDA15qsY6IBgCMBFuQO4/MyobZGK2ibtn+gHoXYjvsgpXWQyyjpbtShzP59eWuCE/zjWorDzNqsz3+vB2WNcCqSUpacoEv7NEXTlWLvBHLUjFsBzdsrUnypwNYoHme1vXwAlgteM2nqWeH2G4Xy69sC+a6ONygtb/oYzv2b5EdPO3J1V774y/FoVxjYCboBU1zdegUzuipSJ1EnoGEakf2+kD/FUK34uf4vE/H9fdp/g3jGfY6hzPuu9En/t/ugEj3+WhyBwRnpEc72tI7XtS+6AuAiEke6cQgVbzzePgbzML1hC+O1y0pA9Q+Y536LPUtPut+2aEAPLPFvuU+jYOqyXWjKGhJBL7uWETkyC4p5vbrOEcrOZ7yw0/QFDW7m6Ra3Vp6VyKemRM+oSaWmGy0DT2zLdFq8SwByGT4ObQP1Bnl9HUTEUKEPzfDNEj3PxeW/4m5i+1+oKwdb38aNPawaQ5BKn9OweKjmOiFip6TjJokwag4qi8p6KXb9eRBxX+HGTmGnxrd8SPhjLCk4De4+OB9xgkuOdar7glEP3nx7aCkkFxa+iZEwbwZPZlkzGTNO0lLBT6pB/NbkpShULv1f3NmO2QEX+x7xBH8W31o7FBMO3edAlQprKjWtNlorYD1k9+XTruQbn7UsGiE4Q+K/WxqmJMCt521Zl71JmyQRKCIEX5itT9wveA7AtnrA1R/byH0z6YFYMzR9m4ewhAisu9+mHwHofcENyMxHWrjnQHkLqAR2eM3FT4yq8SOb774yBEdKYvY+7kKICvLH0ktol7ccDFCMtW/RwsJC2eSUmeM5MUZYLvyPUuC2NZOjq4u0ud21d/Kc5EkFx/W/8xuTE55cBB/s0q8Mee+huVcqZIxbS3R6Jl+7rfS9A52tYAuwEvgyF0+qeDDk0DFED2yGTRKIICf0yAqpE+untGeXI1Dp6lw0+PneU8S8lloweVgGjbyHk02w4ABzpu3Nwer8LjPnag/dmYgQ7rIx0dStBbamuc6LVn3VaC9Vd6xxyyScIGED69kp377ucNclCBcgqniOdjFVBOIy3szwfVuSHmGwPhF6JzcBE63e6TN5eMIwaMh0eBPsLhrO1g6e4ifEAHpOAyMyPdJ6ego8v8fzhOch8y0WnGPVlLZNZtfavVyPOmsm9s6R8UN/1t0q5AuZ4UGdZKjtK9YdWdpfYFDJfF4U02fhQvSnDj0zL/UdoXKFaC/9YB2DIUNj6wcgcUoCekfVvupGo8kCTS/urBzBiHqdhtOLGdoVOM5FuZ69HTJD6nYMePtX9t9sq65hA1Wgo/BIgiSZXDLMgNGbVEwF+voiemxziFeusz7UMC2zTOiaYvUokYngjSt1rzvZKZwKzt6tKxCL+EYqwQpNspBuShQeQYD/NS3SOTvQVtQgJFp5wljzL9DljVO/jD+vSI6fGNUexyHd88GeFW3OWDM66oNpO1kJTgbvx72Roii8wYkD0W0wKVKcORaoojmaMYQ9Zf3cjIIvULzEaEqRgwzqsnjhn4ydDBcCiKu0ntxcr3mBmZ92Ip+4rXqLVlQOyaLRCfgo1eW+raVr2Be6QccVu3wqE/vEI4VKNWIsvo+U7ep7Copw6odY9vp2CXiJ6jG/j/CNEUR7IJXd/rdtt8jkNmzJXsxltz66lW8YCWH3k4nQJFg75i+1F7DleaTo8bgaSGrwEpfiZkGvVKQmtAtjpGB88SYeNnBNoWXrDqSPqNWQb1aJWc2SWntZj+OjYeJTYhDAfUDwEay7XPyc0RKWsV+6W8/f/Z8lxivs/6IAbxb9ae9ao1FFRhPOqDXB8ihwE2XHPFrSb1lgtE9eAJHYSEG/L0O5x6kmEMoZlkC/bd/3yMg5Jc5NGbDzJlSnp8aIMiPxhYytzDkmENEtrACTmlX6Ub943TvZh7V41s9/TbI/+c1eRqNmED9wDRGXLyJJT9Iz6nxqz/pUwMQsvdnuwz7lPBBzzGmIrA4JkdSB4wzQU3GXSA1v0x/BrqqgpEtXh/dsD5V5xzmsstB2eqBSwRWSVscISMvhv5z6d3myZ24WUaVexHqMg3Z73Zaygb4LzbTHhED2cI+DRy1WeG6NqtocM0sdYpppuHEemuVd/aKZbEVKOuneFdBlFuoTlYxtsDsqtqotukmNTI+oZdnsz4SZQDWiY74vri5pNxde/ZMM61DE4Qi+9U+ZbmtsBZwBAiCRxv+/dtqgD3ZDM1OXiIj6UbHwJ1DPbCiQEZzrc9OTD0Mi8DdgT+zC1hCcZ9h8/JRsihzWIUPBj3aI8/Hx439sT1pQwLcb45GnNbGlpEapceuQhRd0Q2VA/Y6jHTR8R/8tkiYWp0/u0MHmG4B0buROW0qMtszLpLzDJDF/50xImD9p32QbdLa/Sl290fYLXPbRsD/ERQMtoQbxBSkHa8TNkX8KeIfqO49D+/kwDI/OqlGTiQdETrxD5lR+Uwv440P+byhUWgW5lmcSBcw1UA2njKtyfGCi8yI6r1ESh7EFb32B7dhZVPYY3Jh6kmwROT/yZciWO/UwSapChe7/lFLPPnrVRe2jciEVXjO0tJ+igxzjDBO9PALC/KS7N6hrYRWB7fqtf8/F8OiQ58O4Kdhyuud0ihs3Dpotry4AUsgMJwz0Dc6BotTIXAJR1ZNpgK8MDpcZtaXMqBecIWHvLxTay+DG80cqhVXBM98xaEdsU+WpIKL4B0MX+cgRQhPyKL0C9u8gpO72VeEkN2UJGQM+cBBP6KG+5lMzbtr15hFQniITodZZ9mMYdWrubSSo01WrmHgBq/OFmdmxkJDphzbgArDtMw0mX5iL2hGCynvRj3sDVoJi9Zkx2F02MyD51/lY9m+aGS298l9Qn7wIDhpk682NrCyXkGwTbipW6QjQon3sguqe43MrXMZIC01fQrBDXmtQALySZNeGxjz9/F6JBGDgvnSUn1nyG453hGakI3O2kxNlb6vNE3H6EBPwKVQF1koHDiDk1wMBIJmYkob1JU7l6MAKVsZWXa5DKWoTLI2oCxImQCGMj6bEp4lfoHV3Q4hheYsvugv44AIKTSoMRit32HNyA75+L6YdYZ7NDvQ9kDj/i0WAmraBqhhmjDaN8Uj5libUxWgxG435SFkNMY+0eMbvwLL/hqb2TNLfQ0ox6u4e16nAnBbmfJIhhKKmhKMyFBcvexdCnTs8rvMlN7Psw/BvBed8MIjarAlhF1srHQd60aHQFDA9fg0z+v26BPVQfR7k7CBylzM3a3YiaW+Pg65q31GafqSeNSdRXlMpqYFw7eIpzBBmBHzmBc0TQRWGhCmXSrwFid+kg0/xqbQzzEGa+Qbn85NCTZcXlMc5/TDcMmEidZTztVOIZDDRtbMBIJVZ12c/z2/nUsMAhaJAyQhImEZ9vTdQTE6zXuzW05fq6mX0aM4SRMtF4FVmWTaWKQ89e2Xi8NSxKvnzoSsiVy8ZhwSn0/EaY2xyHxoO4I4UHMrKmi5R6RiYv2kR7h5KEWbzcMLubyjPaOg75PCM+EPAC5QlP4q8vD5+YIWGU1HxavCx/oblEgYDUiyMRqANz0MpnUR5RkgwiHO/+XWWApSiqtAnB1hwuJp4rE1wVjkD6+vBk4U/2AlatjaoTq2+q8QrXb26lIhzPI5Pwo64+cMEZyx6YMU4D8CbCjqtAM9lpj3I39cGM3qg33BcY6sjwFSU1wnx+scZUCrGnu6qgUnKZryl2iKT0Z7lgMoDPJ7EGoLbuB7VhrT8/Gr3hWSUHHPQGpDanDJUavxZNgYhRVQlvyKtrhPJeRBv3F93LHD9ryAYmd/tH2lEqppxsiPNpAElH9KD4lfCU+ePM7ptsIf+wL+ZuYsELXRjdAv/snlxJVLTe8VzoEcxhZygHBBFMhEjNZEbQc9xj4FZ2lNDGXAkYqDve9R0hPIsjfh8ENiW27OXeGf5SpU08RhqcoL6BP/0SRGR1mQgyAW/bRdGyBYByyynzmGQHebnR5e61Vlv2KAvZeh6W4OBRIe58rW8D8jhvMxSTfd2S4/yi4OElvZFfXgkrraDMpOYjEkXv7GN6GpKL2syTOUituLbHVwsZaFppAijeH7AJDVRW0CXTLRM8lS8cREGryBPH/1e7MHfCiEltGMm+mGKFzS95m1J7kookxEwsZHJnbRveJKCrzOYhaFMu9366Ptm8euv4XPArhV6ZCw2l7kj/LKvNs+20mdRM1264DQXCmIhu2ht8nC6KI3iDytP0nkf/meZCsm5NLs46tEwflyATdX86QSRSFoRJFv9bGwG0RavcZMwbVRVFam3cBwb4jRyNmHY6GpGrUZxeT2t6Jdj0+tckx2Eu+BvHXYQrghhkeJ9WQzlZv/3nqy8sm+qYPWs4BY+MAZZsoNbN71nDBjO3kZC5OI5/lHikEKgv4vtvGKr8pKmmn1JHVYLQW8ZRdzsQe2I4dzGCvyORUc+/dx5gRy4Dsu0Rvflh8o0RkYBmvVatDTD0h9rinSsgmIB/G+YW8WgwWJYuvBMdu8msG4K6eoRGuI+8BxSN7vXOCVwASwViMfxuXbY4dB/Ja/4RbB85LAcG/yJyIYGclQsW/j1yjfI6rkHEOgfAs6slMYKAKp6kTL/sWTT/1FSa+R7UP3jtwI/gMcN8Ml60vGTNCEPlUWnu1z1+5DCqTgg+rwh8vm5Cakvq6z1rmBVA0aBBINtztw/oDkDNVaIzr2m38htuylBGYBj8Ac0APKFwA2zvQZUR0/yem+TCSEioCizC7WxzA4wybV7EDjqWmpsXxOyOkPTb/SJ+ZVFzxA9NSClMxGP8rjJp/w+Rk58OSHKgObEyXqjqV4+Vdt0Jzrinw/PEanOzC1jFPYkvSMfcFdGtjQzYC7baZwnIhSFxtVGbZnTppUml668T9MaKGdqLusXOtOFK+7h8nUVzFMo05hA4q5TsKG742Yzcly85UQPuWtEjWonRcwu9d/XaX1C9nHMdvHGh8zybFYmrh4sfs9LVL5IPseUQ78EDKJd0R3Wzi2lFwT87YsbrWgF98jjDiHCpOatfcQHnPUaRolliaTQKvQA6YkeIUwhqkQBy2rvd020k275AoHJPtp16cpd3Jyx0w3mVcZZ6IwEziWXwgZhEoryIq0ibdbESieHxE71tueC5SooUIRWxyf1Cdtu89DVTrvF4KXpnH7wya5bkEqwCud1uD7wG/l7XbbXJJUb8KDeY7EmTA2M1dfm0hF8+qhztthRIv/OJeQQM3RpXnz1S36m4Nrg31PH8DaeT79yypvxF2LwkF5BhcxnGxIkXhNsZktSD8OTP1X/MHYFduYsBOcNgMkIVUxhNUNN+BCwSVmQ9mxKP+kTRNUEUgdHqD5RbGUCscNY8S65AHm4TpmTcXsGqfoXpYyhQWtk7ol2iMp8kFRED0QrCl+cbSmxgENGfAWYP3wRJodyAfMXwhVrwSqkRLHJXesJKgBCR0sP23V8dA25pQKON1cqXGtg8xPMqNo8AYHMIqkYFvM9aN2c6QZMSAu1Jou6GJFOGzs8fZXkFeBRTTVU+y/EZCFlHdkdRIYVR4MHoTiIGFCb6Ez3VfwVuimFdeG/Nxhftu4S/j5CItVtmHCCfaKoDlOrQGSnRwuS4Wbe6+HAB9rnYtBN2m1YffgWEmBxld6c38qiFS6hDe7iW2QFbmdoYZzoCkXRdBeNIXVKw6sv1JGvkcbreMHE+0YKpUwczD3tROMKfpKmOt4JF84YfcPYHfoYKBvbzfdLxDJaO24yJIId2kwNb/kxIoyVx/3OQFe3zgi6tKlM80ExPXgN4fDKg02QKaEhQLDiSG1uhjvkg278EVpdhoXHf6iyQSmuvqcDaElnF6bmmPL0h9FFNyTLC3iOT0kJJdW8bEQuHSkAeB4G448037bTBvMS+rtYjgt2wzSe8UdScjvAeKLhd0hWerPivQapO9pqIRhP5mqz840FpEGS0dsGsNEtlGmDWpt/UOoEGLeY4f1UO1BjdrRzOYy/bd12ad2qvMlhvjc2KKUNWjJFuWjGQcCiBAG+4JPO4L6+RiHXrj5+D2gLimHAmgl3uqSI5fJzEe5iVu2q5RfvTIjXnh8qxK9DC1GBgj4G63nlO1dcEPhra4Re8UYXsYXvwpLqzl9e/BJtLUPvBNPDsorHtnpZYTEl25FBUYNrMVVrY0RW9n8BBsg3muhXe7L7QO8GMUFjL1iKfxuFkSk6zx5FWpZSV6/gCLR9eOzSW3lzlxkOU2Hqnj9r5o+9T1Y7IAQUT+YVOvvTuyn7oC2h7u20TCodhB5ibMoT0dgGBqc6iZm+5cqwbx3CTnM8xWIYJa7ycyrOcld5tRsrsslDdYAqCxvWIAAcgrmKf+5MBRpkg93XhTrGe/ub7GkZ5E4OupeQjSlOglIceprNj1lSc3SeMgp7GsDi4Ad8aVJynKVnN5YO6cAiwwVDpGZBKteZkjRRKixMLpO7UFpm9NwlLg3rptAjKfQRcwIzPhYJdWV9iTft4QU2JCV973D9po7k3ZhVDBQtvjPAJQyRC9lvkXQD+6OirY6hr8HvxDs2YC+m0dnycAAj9Aq+WD9jIr18sKxP8n/pNf7cktawJLQ6Rs73rXSuA/LayrSsL77a3FxfM7fqlkilOpNq0q40Z6mOuxuo6QxDRFbr8FIGzOlntW4lDzMNUpLNnu0gxRgz0RkxtIu8RN91WF5JbZzNwHREagyxwUk5u4g/J3vC7PZRGRGWvnmAmr6mNY9DEbpIMT6vLjpqAFupOeqUS+LCPbLI5pHt/VzWlsk4ysW0IP9Qc8R7WzgTSc/NAnFrjGh2DfTEq6ihN0cdzWqmUNI9BeXUikrO74XNebBKL4oZCZ7yMjFBHIfXoVGgp8n+4qem9+f4+GrAdxpk+/9fU7PzGzxN+gsHW3sLirJeahp7nXhCWYq0Y+raVjvuEdh5UPW2ISlOybUIPJ92uS9hfzVeUgPZGdykr0dmbgCfExKwYB9QVntLBYrA07NuEM5nO4qXAIBDx518lFcJYMYX8pT9PmzGs4rrnKbCR/5nbmFJEm3rcDFP6n8b1LbesPK8VhRDihViN6JmiaSqdZF99z3tHmEd5Yvki1bptZPipix/XMhx9MZv0yFvG5sYue+Q0fq9+mR6yQtkSsRLzXzEquRqJQlgEn5SmhIEY7xnJ9lYV41DlEUtYAGnecAmUmw1hj5NYcvy1rMF5rNUSVSUYer5LNezoQPwrQzjtSRGK/2sF5BQOf9guiKVTOxbTAtAFf4qp2XKpUtAV52S3GVTAySZzii2CyBBRyor8EfDrXqZpn4uhfcNBDWa2gFYBUxXIKezHIb8CEPkA+Rui4sMi1ANsWby1PzvncCiZGLP98/JrDFzsQorHXpw2ohdQNkIm68ZSdyb16Vv+w//wKA0A+h53on7hztT/0tjxYLcS3dBtRF2Ka2kAta/gLtGiKwFFJkQyh0CCPpPMdfgtNonB0H2KUjeVxPH7IbOqLOn2cpi+q+A7ou1h4koaFobrDo1fvjzB89U2Mo1JlT2QJ3A8COjzjOrWOqZZ2dMNS4TWk7gCob4mEM6pdtENXRg5vxp4WYLv3WwULPlWIxPjmWghPoGUYnbE9LCMq8sxhga1HYW0Dn5Jr9rVmxgnmU+1z48CEomLhe425zccpy2tn7cqMql3eRSLHDHHhhhnLtxpHtqn31+GBmUPmJ0jO5I6PwIvx/ZyiF6k9IxzA/sWGfLJLzXBRxd5tdKHfRB0qC9994xEVzfi/W1k4WWiwR1cox0/jgu2+nIQrnBdB1slLk+bwe2VSTFDKvowLhXcLZ43ctUpCDglQh+9dGlHV2NjsFi06sB/l/8pLaNZCOiD1k4VznBTsR29j1R03KEVD5HtJWJOtt+MFQWKxgfIPnGFxoBq4gm/P4gcKhWb/aqJAUqQFumRYDGTisflyjLiODnNNv15/OqUfOzWGap7QOeUAdY+4dMxP98BXaVGqJPLUFuiWBTLPmxbGMcit/W4tujZsYEIJtQ/TyYiXMz6e3DP7KettXNY0ns7FwAHRWyahpgJC8DT1+859LR1PF9XfrWk9fSfx7n4uHpjeyyuhnNWU8Cxip7HGSd9lGdyRI+GX7rPP50r7PfvagK7dzWie9OBw0ekPb2DxgM35So36lVn3wUEc3PbUDwpLdj72/7cQ9WbdVX4uz/agp0hX0oXeBPtFOlaVlWNOIctGA2Fe1jcaHmKxs7yk2UmXmW5FHykxu2f4mNw+65vFPVKROqymlsqcqLccHjqg3OZRd3axkklWDpX3Po+fQ3Fuzxz3Vw2PwhptoSdO6vDHuBr9RJiA898W6+/YUQE1xE4iCswXshYuI21yFo4KOt1rsiU0pSyNr8Si9D56EB2qpOqfse+VCbV/VVClJepVw4y0QcuJJ1pSKkdjkJGUiQHWephc6n0xmN6vdlVY/mi26czrTwik2NKK6pY5ZEwRsS34dwhqPvP1s4CvLyyG+igKezjsDglb4WjZ1vF1kdcIpdQOvVEtckQFkLj4RF8q1oYOaNlDNb9Sx6A/78GmzCEzIoSqXDlcoWCeqnsWTdyU4GYiE2jl449UT6ETMldb5Ks5pRtaMbfdbBtxdD8ed36uXOSNleRkukVDGsaWbPjDI8eGkeNKHjIRj/kiopZzs03bRGyXsW4I8PpLbOtGRTY8VU10kLWg6c2RKhr2xQ7bfBFi7moabAaQW5nVtrWV9XNNU/0soYOrvrAQHx1mpqR3vSl70KR5JulGIr20V3oQWhXamNarLqXYYZbAM8WLtPP9R4pg8SgGTQ2VPBmn0DR9SnQ4DnYEQRZc6jO3ppv1J76c0KUaZVtPlKrecE6vFfJUrE5SeV0TefO3o7MdShkLBks+iIpwYQso06qeyUJAtAHG31MtA/Z5EB9ZZmxas32X5TlYNautWGrJ4t6Pq9YJ/KRVAtTjBEjU6hQ6TWfLwsQgBu3sRlUpuR+gLrQfPR5NPvq2quRZwTi5tI+tWtzObzPPV93Bz280PsBqnHQ6V/ZOIZedae72CdTh4soleUDeIoBN5oryuCbOz8uf4497TtGiX/R48uCF12Oje1v6lDfnET2tut+CV/NLrU5DY3IQ6c9J/JNQnqHPBfcl2XyX/t9T7covd1zfbysHUvg9sv4309QHBQPTrYEEqB6DgJ6aEzrVaNjhea1xe1tuiHlsymdaeK428e1seGOk6+8D/Kf9s1LAMw6tRUz1wxw8xeyqhHpzvAxNMNYKZILo4PEM0vvtlKU0vGbVxe6opYNVbkWOMF8ecVb32WACWKKLne/c7Sc9LNz3eujzZW9RmUvBpV7X0F1mXdD7jM2ocGmrUxnRpBUvZ/IGURmREWIZF9YOG97JbP1Q/p5mpmzqtuvOeqS4IKH9FawTsR0ryh1As6bRH/M1DtATX6tsQ7moyiIeE2Etbe4nLUB8BvnE6VJv3lfcRffaZ5g4HnvAtzNQm32m+gUo4HQyM3lTmnic/vTt93W46z0kp3aQeitk+Ya8r17E1fBFQLpnBfIiLllkOes7paSnkH1+biKtQWkcrN1IvI3oBX4kiQuyw8glVUW3m7k3cBJKSG25ggxlbaQgFSPG9n9SEHW5cKNriJTVpA9fnnc2yeDYYT1tPpmZE78FlmhD/8/MC3G2NCiRp9kVQqAH18ylCxNuWN/gyZGnRsrtdk9iHVnkyMT8I98sgd0ryKtrt6Iwtu6J3vTDI09orkMkGM5SEC+wdfVRCB6RKTMJ5Jpsh8dXAPd8/mb89O9Hdv7G/3AAJm7LkemruSFXOZrWQumDee31nkOTF09sSEKWbQ5WGlXDYlzu3ddDGhCtUqlrAK7zNlBoKO0pvwr60cysFg60wxxnMKVEAF0M/FvBxr47uWM7k57NqE3tpMCMPwt/KQoEe16k3/h2j6D+ED/q4298o1MWkhQlZk55sRDyc0NuSQ4DrMqRt54Fzh73PrWnEYzMgIvRVy3VQ+xQbgUEjJTzqeTv5mvre8RJ7beq26+qkol9ZzwqMkRhYkTfyOVZ3Dhd3/hpODz9aY82jirf6B4xnyxWgrKXCZKRt6i4lyOrjHGmRISgw6JFWRpqVDraw2CLabp2FqUZUv0TeAPD2pwikk6Xvhkxic8OWyia+gyVpwb1UDOHN5hQSwlBuIUug7AYtHOlY9QACY7Vc+G9cf818humb5hR0UpUeIdrXfraHUQtGJ88db/6+kQRwtU+yQkUp8318EMGhKD2toM9Ks48Vf3a3CoFTbUySGGM6Jxideev5V4ybSsvyuxLLkdqd3I6Hc5bYTWQXsf7uUVndSw3G7zYiVOuUl32/89rhupIW856wjm9e3NRiE20juN47sbdCGAECiP5YCUmu9Fn/6xYYDLhQdYg0ZftwGUGpOKK9EmKotNob7ObZd2Mhg5oL1hL7g0t4M/fJxF/mD6YTMkvC5Yxt3JZ1HL27W0hiM/fykjTXOHD8SPat0dwHsqdjiWqGFuwUgCmFSfnVeyfwgRIywMv85Ysw0AvqI8PvJTlsX72AkoYxleA479h9//X2fIqkzNoK8mYZLxTe30VuYL2rbd0hevfCjc3TNtktVn410CAPuk2pzGzbgk5EcN6hOO38vPHOuqEJSxByJo8vc/ww+4CgY6Lm6dNO10cVOKnbCYLybCg4VPg7EGSRYI8XgLK6OMWCc0igdYzBaJtrDbh2X69XE/K2o1QbY/zLuaPGNqsmZLIEaw5UvcOLAIpenmnPuxokq0oDGlhUDbVPw5NnHGrz4Sm+bS8DLuAbmRpIECOvr7D8jsVMW2nywIqlxmHzuriZUXHDLy9wSHId/QfAArwhtcPY+sWz30LKQ1JzG4VCoc5j6aHS3wmbJI/76RuJNiikUxOhII9t/YvFNzPzeSrd09jHwDUIHeUbfCsDKwW8AoWTtjz4GxrR+xMQbGOqO5MZ5JOvQMCfFI8PSdR1I0y8CHg4UHIoe3YgsNdj+fsfhqvq3HYECAjzk44zVfpUpCJBsLv+T3QYnZk5l0sdLRLjK9YGkMwmSB3YJSgqwxdQCwwSDDtdere5pwKoXXxjn7MseyK5JhZs5dvVTDePVXu4p+ZEWfLzSQsN12gFnZCcSQxF47XWaEkkDrcZk5YsoynlZwWiixYlnYLrFJgii/TZemRPMDOds2zDp1oOiJBlUhXhbekfXN4qLQODeWad1IF++1IoDloh340PcVxOKMgM2g4mGN9HugtYEdAq95p93ou4r+mfwPfkSkJLxJ5wNQScRaQ1zMOjy3EyAIAiz99hybztBfEYTh9HYjJSC0CWKxTQCzgTqBcFk7tAlyi6Hz9ARFnNm9XLcRJzU+QSQZIcI11xJ1reRnFYkmtEWcQ3wcXYnOimjoqe4xFIvtkiKjDhRMdDhJwhRv9m7kfMomMgyRkeSfYahytipDz0QawJYCBgO/DizUuyi0qCg23kmTnsELfeqIMDtoDuCYA37EgPxuQtnLTn9M7x3V6M5aSeidxSInLshD62AkAzbc0jQtR1vOe3UL3biYOHW40CcXZY7cMrl92lr2tgiCUeGUK1baFUcvlRlo6yKkrWQqkH0QM6pPdKQH7N3bEMNxG0OAuT0Rk0szvhDhuKh5HXgvNWmJRzRNCHXfP1Q4cDKJlH/suHZURoCrh2RQfUq5Nzo0JwIOlnB19uQ4ipYFBpN/TExaE9vn7Ki4bTAKhwYNe8TNZjStuDx5uwvkbPIaYGb1E0X7jYwg4iC47atj062mDBBSRIUSZPbb/uUkD3th3APaXnLFWH0y2LHhttzee8NlQI8Am0EaURLbSI0jiykv4/r9JVGS7K9D52FkrlVTZztsgJdt88ukUYqUL+WslpBAQLEwSDKjjRzfb3UO+2L10SIL7HAsqRDs39X3ztLlch+LgVYRHhC8dnCkubi8CmAAVPh561W7XRos+oo9cWaq/0cTDQvvcBZvEGeGWXJCGYRE+chWUNDb326UHFFUjlgdx+Mn/xlw71JBuSKg9tmHPJ0mimsZihC/BoGvBKRPgQU9qLrC2DoUZ789RKhqWjnonceQTFqdjruWqbgYA3V7cK0lC0g0AU/wLyFqost2Miuplc8vPFb9QM7ubixU7ZnaB/rtdiW4D6MLt2ttqLO/6gmsBc+9IWjOtm/XP0MhQgoIYBI8pxbgoKvkzvwRnJX/wXimqLTRG8NsmSG7mYP+TpOm9vjLJwJKWlyacpuTADkyvqzMRkILrzqLi4ng0XhMrqx+8iv3gyrMYjqfgZSksMUUqi4FkJLgJPZRC9wfMteaBh9dbDwqM/HGrVRuArUECXHdDjqm4NmIflrn8xpHZkmkmPI6nE7GG9CQw8lyHECHjWODw58iMODANMv04VKmn1TbDdvSXUbkWvJ528QFBDFELtR1Ns1a8gwxCtdwsGmquXOrESoyck0N38tk3VSmwQfd+/58hxJq2yaKchcjHrBT/cZj79aMGucTdv88wmB9HO7JjspLH8f3kj/kUe6wUGm7Z/AJ7vmX7btg9cmsdNNlmH50PxPBe3kXogy2xgx2Ub2jeyXquOijVLrfKG/Lsa1SrNOpQb1NRKbWRzz7qiR6ujrPadkyanzFXtciSuAGdzEWTertKpA1sLpD7z88bEg9JQG3Q9fhXz4NHlBaOkoRrmS8gT/Lb+j03IE8qYX3AKACLqoeyiiqntmrrTjxvLW8QlOG5Ih7/h3D6p5jMTnoOoxehmV+FD7DAet8qtNcfUAvF9v20tNgk9/uo1Hn45JW60rltHkb9HP5ODL5injRoDccVkXuLJMEW8yV6JNU8Tv5Yt+CGYBJK/T5lgSO2i0zT5ryjcdMk1VeYldjI7aIlEPSGj54q0HvEy9mOLfocPL5K8SOz5+etqkALyHA7VMdLXG7HjWK3SnoOz5RrrpwOEz4jurlcrEpkU8z9cSRTwybLuFlYEENEMj7TMdLzEX+ik+4MimdL5a5/ahT+BiAXcfgsp5lZNO0k7MIVfAZKM8L2OWLpmgYCdV3PPORrl1AkVgyB3xr5BiaOCV6MqwxCwDBDRxuM3+Q4CjBUHr1YntGaqLzj0T22zo6K7Qv4SjTmLc3OF0lPOLYcf3DAFoM26BVb8doP/Z1Xl8z6sZ7Oij0YHmIv/5q3Pxt5auFwo3zWu9yT11BYFrGp5RdLX2XtShqrO0tTQz+BBbDCiTtTMMOapJj75r5cG9tEPxEDqaz9Ukz+IDV882IUHO4M9mND7iTsHCn5OzmKINw81o4Q6HQ4ZBSJ7iQfw94SA/hxYMirwFlq5pi/OZz2oMt4i51kT7/KyOG+nwuzYUwFovGiLfv840zKYoxXz7kzcRAzI1On01PRvKfLjsZnat+CijCczMscd3NF1VZu2cSAZHNgTmQMbAOsnduAZT1LNVGvgER0QkgMkuV9pmZgjYPT2OoEUKvB6MVFo8/G0cnIcvEk5+4T17Ad28A9+36HefM9azaBNNowEU2R5bDc8bcAKG5jBxHs0bc2J1NGjeusEH+dEZMt2FScbktyUUGFAS9mLfLGFd6qmP4AWowSmcJSV/wBifND63zhbZVDLNWLq9uBuwwqf6InQP/bTIAtwu9Oqvg3HLa5PKTgKpXKTT23y2T8YoEGFONoJaA6ggOvRsYEO2DB21zJfqmD49H+ej8a2NEcdm0h8HVC839kxDOOInCco2wUQhk+4/m563uTlDKNeFlgDEf0GKLXZ6ua6g2Nr+Vs6wOrrpgsMSwmnWw55hrlt4ysqM2sk6WwtBiSzUasKwvBV1zH9M5l5Ogu7lAsaMOFDRzGRUD7aqjucVER/7BBOcQW9QEKV0p6ZlvPJUc2HKPYe7mdfIciBeKBHMYnAI3SL8tj1Q+iJC9VQNwuifCjM5THJ523xGRXaLRf9e2W4qD0MaV8A7xWdu7ztMKaX9cZjquIgudxsiySlsEDV6IGQdXJMvBM41knrYOKeNn8bhanrBzw97L4T0NF7Um0rW03Qe+tZyXqi70HOpppPW1nTb0s1EXQvJMhryBhCLP2fGx7222IbuyBzEvidr7IuXJXpsa8I/MznOd7XrqHYuLsHqVtKh5vzXWiJOPwWB+KOmMnvCqYOrKn7PntO2qmiBAyJibABOigHoWuPRfetMbvkP8I49q5uLgHJy0K4zV0WMWvEVArgfSPqb/jYjXtSMsRzJa1AAI9v5dOBLwFLo7990TENaosE1379wLk1lfeJ3goZCdLToqxKNkkJccw/B6XQVSnAK9uZIw18kIjspPKKDyIVhwtU2UNXzbCzDTjUE0emq8gbnd73IlxGNwMcS7/n4uD/5eSlF0zzXoY3NTY+Xrhc8/6kv65MP5rLhOJfANVoY2RCkLu0zP2VSc5U6vFiWoQmHPE0JuFPHJJaWlWnACtMTs3MrPWfmBdVwLMjHkEI1y8ci4xtXliC49E6UxtBJB1InMKGpJyuPEnGRXD161ONLjNFQ2d3L1/HPRUvxiYwrJdSnqpdfZO9WuHN28CR3rrb36XTFVWUUR/w+xSDCOfyVNgUFjF2b6k6VTbXPNrNHKlBq+k/rsfia1WNfipYttMYsv5f+dKR7nwlXGlQMvjiMCrEQFflFDVl8MeahnVwSwX1tvVax1B3UB1XjO74B6Ai7+q+rcOGf8691/JmnHwCtIxt/gXsA4qK7h5ikEdk1cLy+OMNhzUlY9dhX1XQIIEGL2td46axc1A+l/6GBHPyePIMUbDEoAXQPqxgro4/lJASSu0Jk0JpTVtFTyJHhlnvM2tm3ho5ZXoeTVS2JGSrFTnykaJeIlKiVoJbzKWIxQA5HTA2Yd/w7mhMBOJkWrlnm8RLhxXUwVX2ilqp4ae/J//yPTRpFk+g2eilpi8g7wh0+ZSOLDsL9WNq+WXlvjZPv53ujRlcbmmNDEE1/Ga6ryOSj9KHV2UbKdUioXmck3hDcKj5Cfk86o5Ki9faZ3NmDlfOctK25PE2zWRvvAYRnr8zuaIEzxmAaGTSXU3LOkfzfus7HqJToAzjy0MluBJafkjfr+GGDmCNkKxR0P36kb2qn7X7ajIjNYQz2LXoXMCRKVNdrGQAbwP+elPQNCWdrpzOKWSF0+UGZuRYm/DTJpV8Rnnae5vF74a/ntNiL2Yiaa8AeSaTJetySPpGkqOPj0tnS7hQdfTk8stYWomct6l5iIQe/2Bsp35UZ5d2hIER1KboMEOkqd9fooz4OXWMNFgukGBQsEuuYe9sobjZt6TCFzR4+MeEnuxMNC1FbSDDlboknhzEokujMqwIlCuJh1ni3+7znE9ZpZsT94rU7caKrSRL9L9MNZ2ijtFJYWUIvB1q4TT05oc6mek5exug9ttEMYnbRdaf+u/6fsN8dTbDQF4afSVZ1HZ4VSaW7VgcTDQznYT3two7bhjQlGaPRcMX/lVV9JN0/2ERT5auJpqXTOKzvu3XPdt/aHXl2REmK56DyMBqIuyd1mF5btcGuVcS+XrrElYJTyql32IlXCpEckYuMAsdVm4t96fIJ3h67WLLNvWhL6Le81mS8FNaUXPtmPXYydQRahJZeuJUo/0ucRa5Eff2W2RZCJkorP1iLMuuY81EHpUb85sbWY5ZMR45FSj9ryWi27r8feuiwBjisRRNhkk+It7IGjc0kCQLoFNef+CCpWY5jpf8ES9PC/LS11CSqm66aP6mSEv24kRVMCgCp9rNQgXFGn/mraSZh6HviWWv1LwTcS7ilPROVnKwHBuVap56IaDjkWjyuZCdfRrSs/Zy/4NAZM8Je4D30urSzlTdxyLh0JIzWu7WHw0cyj6qyc1fO7OnMKBU3QjEjgLZHiJYMQxX2cade1KI3qaInTyfYXRA2BbwC3FJPkxw6RKDmQjMIwnN5U4WQeY1wSgVSCUPucD8WD9YTH5LsXk9Tx3w2iKwEEB6QPgNXhM8xyMvXyr0zOHSql0QincyJtl8McbawQiAnWTTOrQMLNc0KEezEly9FdxqXGKOeBtM42Q3QQmmcdGzmqvcchgxepmAycjbWphtKHR0I2kYhsdQpgSIL3CggOdYskX0xnAR4hAsCpdFgWuyZUX7XKSg7YzznzU3IS442J33OO6ZaaqvpH9tt2QHNX9FuREqtNiOk2+NwYWDG966ubAe1eB8DKkH8jxly+HgkSZZfIfJPrQZUtotvSNo+UoTfT63PR9XAttm4igyYQC3TepuSMQg12C5TCDSCJzLMDpm7bI0oDu04au0Hav90uC74gWc3zF5hAeduh8xcDRG75OwYeKB8Rc/PCH54AGm6k0hrvrkLJr7j7PHD1w3BcuppdHmsF60iUdV894E8bpz3YfDe2RUj0iRnD+YAzEPmAmKjFwynAN4nFdk99ACPmsc0U5LdIVZ7jrajW+kByiBeLotszG1R9Rz33WQ76HK/1CgFndweAMvVHDrELfSvZNWfJTOhCXTOdSsyuMZWYEu8pN7JGX6wiHIYxRBI1vzN4G/irG60rSJpPClf0ztN4qK1/qxmDCQVWUdVVAZuOwMlJKqZzYuUkqtQYAC0zircTg/He4MLiFFfMhgtEBSh+ZW9DQXv11OKJuZjQI2Ntomx4BtVXQUUQsvZzofOo3BQoaKS61H1+xD25F4WJo/KT+bT1SVExbuqlmsntMhhN/WIF7k2PsvUUIasOKhtJifPbWoGDk3sxxqdOfa2yYbfdE8hEy7FyXX9C4lieR3xcVW5NvVmxm9Q3aMyPAJNNWdF3odJLlZEbXYKWsCKggqSGFSy8f2uJK6/kVjBHyT46VW1v+RmMILVA+1CspSb12+PMdUUKoJ0NQe3oaqchiNt09slPWaiW4c4+7R1oXWQCsKbZu8K11+vmASh1FA6j1X7lHwQSUPsqD52XF6o4IiFKod0LPCVpb/d0vd2eh5JcQC9r/iS8wtZulqRB1dsNlOHlG8UIujhbivCSflvocs+secvhfD4b6cQcNbnoVHO/Nic2nHZoVPjUsHJ0Kitix6yjmeKpayT4tPAswLuwAmeHqmXuRAJyVmCG+Y+Tl3gITfMWgRGAYuV2goXzsDvKYSpRToqawrSfC/Qf+hjCZiAM6kS7VsKt2vyldgFsDcpryeMPEv9JsHvG4DePnAuxFxr914U9TO3e7hpQmwoOQzBYpInTii7+2fRzVQ/GA7VBy/lY2HB/lfQ311+RYTxXkO2FHoTM3xTPGCRxQ/hhkQtQV6tyIi30r56Ss7FuOgkjws+T8Sw5PCYyxY0jfdC/OIyALAzuQnKfd5G0UjL664a0MfPyt2EKf6noLlfCvdQnNBK4mfIqw9KzBZ5CDv+Gz9aWLMLMI9CFqXSDvxVzsfjVaAQ5iNTXeiNicWH+L4vPIup9cpRsq023dOhL7WZaoICNDTOjJkj38N5gSs/F3bMsK2EdEbWf67BC33KmzBWwGggt+IZcGoO934Efl6O8mp6fLgMuUAURRfbrF2jMtUH6ob7bvJwIQDxACXHmXoVTLIJPQKM8ajFS98nmwCu+gXh1OlO/2optK6zxZuESrLFggZzqStvP6c3kJXswIX0kpxHFXQo+allZRQ1JpwFANuPs6nf51qiPgr+pm/3MSCrHDJxOMJ10Wfj/xh+QpsEUNV4yRd9/fOoFK7ti4/kE+bHAQqusoua/20htZd5+acMB/bY8XgaF7A4JDIOM9nqdzn1UT852JRlAdANOsun36eQ47pNOIr9Fo5nnkmqD+90O8lzdKTnBhiKMPHwAWwmrn/GSM+cb+IGZMDafRZjTvfHc7Wif/tmw+BpUZYdSZmVM16Ea1e9j5q1WP/+T8v40oFyuz0qzGogeiQx6/RTw+KH+MG4GLFFeSqEAJ/Yk0dB3qVyqCHyxFnfAZcrtBIyGv9yIkjHBq3E8x6J7PoKUOSnOFp7O+xqFwAni3rUCIXFaX9f2+Nevthgn8mnxAw4LDYCfq8u3V2fxgrPvFPml0tipH9ROczHWbnDLxi7I7dyhoewDjXApW8D/3bsLfI9IJXLhJSiIAye30PLsjKoF+/Cryqo3fhWc4KUkkLmMOr5T9YO9tbv8ad0jK8ThDl8Vf+B7VXyfv/3t1YGmWlqTbQYU39UhaaiDJ8V9DFfYJYhBdrLmch4yMeG9ihL8maJdfEw96m6ba8Eiz4Hrx39IkYb1v5m0exsdr4jTsAh8b2UiX+A4urvhLHcX2/rSqZblo2R7wOIBN2PmlxijVOFqN0cf3EmT69uS0W1y3Wad9Gc47BN9ODHOc+PGMxQirh21d+kB7n586SqV1jeEgVsRVS7yEcT8PPpTcu7xr8ZcQQHNWjALJOELKuZWM1u3lXiMyq3NZ1fHjgXXqIaoG+hrMOPuiiLkMn2hgmKzRL6/v56zTGMVWHlKrM8hQiDNsfHrY29h52xTm3o2PUTFIOmgy0cNwhClfpTZD9fMGdqp52gNDfKqycAAyZLpeglznfL8gK2NuJdW+SKOGx2sLov7vNF77D/WMopSIorLI4WokgTmNOSFePPYTlDaAvCEQZpN4mmmcs+fVkIK+1JRpFvBtIMw9twrLrmkKW9LngtwNoiGdu7ywCnbvWErDG3zJND5I9/GZC5HbS8PjARox7qBmC+jeTv0C+N0IdQfVfr9O+zdvbSa8Ba8ytozaW5gwYtajEUiiWczQ+tiluHkPw4V3HfYjgHtY1GgWSNx9e/7bj2hiZE8Rk0CFXVGKJoaryb+cE326LnRv3lqfUNjG/u8auJ05AtyfpOT53Z9GUf4eY1O+UCEipkTsfMTIsFQ3E5Lf59Oqonkvt0hCBALyr6ceNH6jFBjhnSzykP2zpAF6ex0f4WCf5U1PKAAsrepdrnC4pJo0shT5XKAuHRYOsYDlI4PUl0P6JgIR9l6SnsvkTdoiWyCxmU4feIAHo5PaFgvlPsHXwg+0tooFVrb+/2LVAZNoNJsuWyQUmVt+fubbgifI1jJTf0N2vQqmoUg6yxGcN6FIIHGzobHbTYKQa4/vjHtb0908QVtB7t23UVsd6Nf4/gQcoQmnnEUcLxp4FQvYpOe7B89A662tMU13g+sICABYfV65MBbS5tP8uYDXM1mEIwRrgkCMbEpIWhi9/o1w4tOLzGzV5HrvvQtFACSIHYRIsZgzQZvNIwk9b0qRRhPGorCKIKo7kFEYNtHq4DrgXW3jJSnpBJvsHBeZYDxaxK2fWaASlcDrDydsfMqj1VZCRW55Idqud3yqLlC6Vc5QAOzkIKGGs+NUcDrjiyNMa4OOWVwsoTCP5+9l2gOZ/K+5GVYZeSYu/Pt39QWwm/Iwiwrk+uUoJIy8EXJOnGHB9lnluQrNpkLtvHtcaKlJEBJ+Bxi4mlpePrFkicMb3aM44C24QLZnNjK6SPshRgCJEvdhiIIr57FEZa5/9O5boCQHkAZxDd4ynd7tC4ZH2DRTXMJhn8VxBEzu/IsuQTsUpYasGtTH1pQAsWEcXZ8+dJkf9zHaDwYAKru5bkK46hfshqh7zOU6CkuWVRh9z3Y8DwVZR+AqG8h1paVLlK736ZrLfrQgygU2quSiAaDid3DzXs6KjNySUfkJjKzrEBcs3IuOjj4vpdkJxXApptZ0/4riPLq5yDeVuHKlMwAv6pbYYLK2tiRm0UJ5f/PbyGrZidxp3Kfqpot2T4GJqyjTF+Y17JJAZn7jAeQWgAXj11koQYCQHWIS0XiFqIsrN5CSDgBuCsZGikFhUv/W9xWipyY+ia9h9Ixw+PaQv84BbVuuZCGIzLTP4e7GcPZk5WqFoZZwcNf7vwkG7QQ1lENDOsx4Eonrz/S9DUPW7vAl7JzLZ30y81sMYBi1SqfT674Jgqi4QqcztfDpngOxVkviRYLopzux+iK2ByFh/pyLYIVJaBEv4Sna+2bvcDRBdpFvF0MJ6Kn777W+l1QpHCV+PEdeDF6GnUIt7aYDggaIwgMyjLcVikUBjZHkOUL0nSwY6jlAfaRWXgFNBGIzx/2u9iU3k/ELbCnn0JizP+Iz48nvjY4txFrrkZAG7uW7L6hUSdCHjBVeftMrkrT3JlQZyzpslz116+o3+aLhOpni3AteUvYxlpXK2dJsYoLZ1G2O/kTtBf8PlEtKvk4sNUUtV+g1/92jAseiKxCSppYgiXPOt8S9mvbP/tALxT3vZzppy67TKr2XtplRETN4wAKmCY1V0DEYqooSnSz5GYh9awYHDBfm2EZ1baaxxSFIAdesLSDmLQ7fSq9akwJirZMygiz1BTA40HaUBhiWbgwSVjfcO5bBb2C/r0/JBKb4WELAfMjtv/L7U2/92VJupxystuLJTXcIGdpNqeImHPLE9/NH6Z1yJOa8DPz3XSDjmcfsQ8Ua/YNW5W0AaM+RlDOxW0hsaUPxoWlBSBSxdwRld3HhtjdYzg0i6xx3Czk1O+LVX0W66/gg3JI9kzAz/8LZED7jcxk6pHeGD+uKi6BW6C9Umzaq4O1QipK8m4uJ3LRFfWA1WhObIjyhO5ucDDT13lW6ehlkca545Jnxod5Ig4mQ1gPMEydE05kkQvGqF0x44nZsS2ehGOFoVFTgZDiYjcNiqwXB6kGs7frJl47DA5tWwJXlhLVFAOpqEd/1Ns5WgzXnqDnVGnUvjFkijdY/5jLniTcBHiBVucAsbJMP67VT6z/ln+quZDeByxe7n4iA7bWjzwF69Q525UvERt4N587YjGnVw2tvSO6C59nH5TD3cQtzvLB4Ikb/XQhCqrLvVxSnTNo+1A78gXCUMXEHlPrf83lRSQuMLM/po6zc1JvXXfg0rvOJ9c11iH0GZOvQN5osyPWa8y1j7RPNImPaLfInY9Iohfio86cKEcInDPizKc8UxOCWzvgp5kMKscUsT3EcqZrC6wRd2FjW/M8hAlIZ18u26Cv8cGDg+gDUv6lM2dLX8f0cWtIf3FRceg9MH/bfVwglxGUCVe+N61/mYFy2HevXvH06Z2chQ22JUhWpPQfnhvRlLRs2F15ADSneP7o5QYDm/6PSTNOf0IaX0tqeWd0R8jdQzY9xAsxHKsIfQoXRazVL0zzvCNMqHhJOOkNMQrfBUo8ceapCr95v7w1d81QbjL1uRehIUM5sULHrF21hAec0tY5OLG3urMq6EURlsHz+PLksCaq2JCuXd2Wnz5IoJR8S31Vj2IXJC8BhG7wbFU4de+zHtBShmQ/plf/ffmlP5AfILxqzhuRn6W1RFNytH2sh6u8C5YuwYJ//qX/AFNo61+KQzIDiwGruYAtlOXGKNQynlS3SqRh1fBEOadweZeoVLDtYRTE7KGgywEdO192gvm7tSMVw8AczxSB2GnCU7uJ3uXil7bR+LHOOHyYkzCB0LsJTl1Oc73E76KCsrF8+ZomdMxR1HrB9VXZGBnbdU51Mp/vhB7XLZZso767uVKRnh6x0cvqeICuNB7lmQTsrzvoyG4iYkNC9jKe50iifJixW7R3Rz4yEbowYtjivqDO4o/PANey7xf2YDLpsmrh0l4KiQDDXZJio6C2xwogDByP5PLGITPXNPwA2iVDae1V30i3BVpm02OThN8j7vZOsMp7ff0Odkm947nf2TCCpFAogYof7hcW+iC3avQxlDWDjMTB7mNw7MxIFwzR1jtqeHodeo8wkC23JWKUpNvlqadlb1hhv1bTSbk67BH/CX/k8kiZTC65dFTV57rJHSAtyY3jNZopBN07lEjX8zZNrmVm+y0xKNBQ8666aJmeY7e85+EXLiZlWZDB8AmMtKGTOs7BJMQN6+59hiTTtO1zABYw1z18R2Ws2g2B1aGZz80P2+eqz8XOv35i49HEmwMmg8FHzJdnIWaS3BfVokcPyDjPl/OrVS3JskI5k1N1wV4+OsY1miHjIoxOntB8jCIk2f9XPEWW06WX2Yvma0g8jW5HfCmYEGwgs6ICe81BJPyLLONRT8SOd4l6i2ZnKNvFbikh7epMcHH4wYpt5tcmg42RMbksWkyExjUtAH9we4CcN4Qe9kuFVt18TGfHudoiNh9iYyW00MIbuP4O6BKXvPEi6LyzjX8Ml7v0JE19cCKLZkXwNpk7Bl5ZmyL9lHilbvTiJV6FBR50J3YXPfZdwwTzBDeF4stBhotZ4TYQxZSKp3Q4hVWEPlP5gRdR165x2nGy57U060V9VQpEggeAtndt+//fvuUO6R74ONukGZDKhT2GFP407GqRBgHUyy2P734PPEzXEA3PcV6mPkd1UDg4YevjPvwrJbSvqz3DXcYvXFXnQkPXFJpOzzEji73kvqbDol1UYNAyLSHVIPpg3FLO8BuF5Aq/OcGyHzRg/dMn55HdeSAB8/4fG/IpaeDIaM523Ln8Sj95ACYpxO/Bg1uiH6B6aptZ/eurNM5npG4hV3D6qTBgL66iQ1Le0etAM9IgC7Q08VFmanqctz7m6NV6wOtKYXfUECJctbWYSCmG6FKyYhE2jkD2NZqCef7dvGnVkFL+b0yEhWhoCNd+LkH/rojdRloyCRkffHxkum9WdO7GDwp3s4WzlQFfqsN3JO2iXQpgDWBPtpP/7JWBLVFI9ZxXX5zeJUOENm9YJMFB8ghJJin5tEzpjKekQPMs85457b8uOQ9v/BWbtgcEnVc3q3etfXgoBy50oJz71Q3vqXBGkwuolciCb508pu5P4qMFulej5aNh8ZRw/8w/tpiu9ne9r/H1zaeeH5qdfm5+TOJ9ozI4ODPRB8RMsjeoBcEOexNbn/+V3OjOYJPT+BD6Gx1o8I/qELv/ZEP9NduL+DHWPKnwp9+fVx6hB/OEQ5YkAtUSh261Ecn6XU0eXDF3qV2G2nnfUvCkGquBacVgPuRP0O1feeEzm8YQDwsMi8eFvnRgnmPj9+vCURESj3vgqVqEGxiyiu2t2nKdzFhO9+CwhMyaXVLvaVkEBIISe59YLFLOYrv5Jao+72/x4VEt4UbeM9b3Wr7FidAbOFdcsI5jZ/2czZJKnG4JWdyHMwvAtYnSKFeSqRZx2FRf6mCZVuCmjGy9FWMG/Di95Kn0kswPptB9a0gU9Lwj8NLc7gOSlDuTPuSTV7cr0oix5qQhxqsdwm1ZrKbA8/7tCWAHkFpkQDCCOWraMbOG8cVWmHdEyCIn1gsvkBOmvK0fcsKC7BJxp5jhglXPJv17pWBQodx0IPqdvgD0TL7zRmj9wgAicCiRyZEN4m1IXFQP418gZLVn8NUL1dv5md3td6KmRVnqROtFjBbeA76T/V6PJFvvFMxbId6ObKELRCijWHsycmUH12pyrowBwwUdZpIG3JkTwupOpUtR/hHm0RTHpilJj1k6vPdYLBD/bbNuMEhGqY54veQapZ+aBx5vfGzIybE4TyDdiX8sHbdTz4nONUgjTueApWcBFjjjRamyvUuiLfuayr2BfPYlP3FGy48pLIJ7UVRE0qq1KKKLFe8zsEMDgakf9YcNKIF+LyDjxDUWvcFmNIL0q5eaP0w/G4hYiOmlIiJ3CN5JjXM328q718PcZzwxbjz87VVMIfHZuHXn1+RtMKFJsesW6N89QYlPWFzHdUN1KzzB39M0GjD0+iLId5LDGHSUGs4cv7DwPvC5fJiv/rFR0zsrhm2ZoqIoy75AmWNPnn1S1UKTDSsUdbJIh1DyHZtfb3/vEKoTJCx4afklG/fhbbfm3H7dohOvlYKTyJLas9kh/ZQ0e5XWO5S2W6y0sjD4Z5OgT7WOA4pVyY4HMkoexd4qgmGmF2npTuEhxymNvHGYohWmSJQYlNnPxIpL77QRqpNFpAbHaqT3Ii/+4FCxiD/L6l//TGU6od0zpUDtwVKzGKh2H6zPMmqPuRzXZEeKgHPaOPrN5QOQKXse7NEOKe+AwuB4cVDFVbV57OOqd4ETFSfVFn09xQrIQJ/cU1n7/n0GreZ6jD7hlBb0KsCpENE6x46zhwg4CNKVHZIcx2lYdI8Nw+TCSSQmNZNIbuQdHB+bNaV6ZvI4YjnKNdyqanivNOpAv80JEQ4GiduyLqh4Av7qS5u5/3hObZlNu1Ev6bdHH8RlBD6/M/Y5PumF7dMvhUReEWeE6b4VJMij1redE7eTeRQackLGqHbRwMviIkFk5SyGcam5OvdPtMb2BwlB1QO0Lqkrpj2aBVuh53m0Asg8NaJp4Z0QTu1MNkJsMebtTnAus48vNYMhdExIqVx64acGICDl93LVUAcjPpV/7q+PJhZLtpCFw9CeAdFFjivRrBaLIZ989yEg9csLvVRB3kNT/W542aXJbPmO0La3B01O5b/FtY+i8l1GRWZsSQNbQ32+LF3QRAcz+N+fgNaHuVta8pCjv5heoZmnZp0xtKs//iJkY+G7PknYaRVDRp11NpQMlFPGdRBVBuIm/7X+xNc1wkiImVM4axrtq7fq/fx7ku3U6rPoZR3pp3gEAdYDBg9NkF6Zn0YA6Rkg7H5gW+DPFOeT6h9FiB4HjU0TbBcneXWewXUrAZ+nH+tciyC2+ZTjflohoYG1/9cMtKvnvfSUapVfc6fuKMTzXY/KV4D99rhe+avIopcffmhAgo0ovHscXRfHj1bUPyRsf3cRF2n/N/mJ9orshIdBjfFdfjYUEK9lKw7JUXQES4OalX632dmkBzhXZAPPzbWHxNLXhiJgaoShoC0GJW6g45rPfZr7qmeN7PVdLSBbEa1CMGIpJBVaoqGjxV+XpFDaO/u97xzIjmHW46Nmfas6NZvmwHdS5y0A2YizGwEbKSMTZBAgZUHDoZb1Vppyc0vEU78m7mVEMYjWy6Cy3VSLN3EKNpVprl8qq+SD4JS7Aj3jieBt4FkYkL6i0KDCzL0SB5jq8L6zpagFnIp+DEq0dDdUAYhTa0PpRNA5bzgmZM6L3LvlyysZP7JwOUh1NvRG7LP0JMUYjlYhQq6lYfOl/PzpK+XsNJW81g7FCeA6ORxLtS8z5IfQjNmmke9Jwfvr/aP52pLJpEulCpfnxQYN/9HZCV3fwME5cZ4bhuQbqvDYaEHasqBILXiy2aMRj+sQ/iEIdMLdbaJfmsKcP2WldeFos/8PrD3iSl1jIR7pyF+5HFr1PvA+jge+hSDURnFjjpCaKDyAxVGvCvjfobbINnU16CbXEsec2yMUgLqKX8GJ2L7FAcJTXRRzlAksm777w9ka/z/TMi1WKpeWcRI22VC2/hWKBEeDLMFDqY4Jc3KQMANExNJckeJJDFRp0+vwpyXxYp296k0WcsUKcVFyP9enekBZ8E+Ybzg4MbZpbxdbDTq5va2QDRAN0wHKOpiLcKbnmAT2n5RQEzqqhWX+yX/YXMKXZEqihqXppzmLeYvGjrtQhUaMdb/40HHTuroqbql+LqhG6I4TpObGWHVX8UdcnfzD0AaxoeEVp4F1KJEFOjMUFbWA7zt1Z7DB77qSc4m8VN2d/f+sAIQfMTW8IqwJGiCzuL9FNCPJLcRbfOC5Rzjr4mjtiq1AsKG7NUbSWMbZ47CfvCk+98qZz3X4BnnicPC3if+aFeuN6ZfUCOKPDPwNBz3AiN3SJ6qnjDknz2GL/fX5XFj4m9m3V70/y9LpcItoLcV5uTEo6aTdq9vQ2OWX4vM7McuTga2RT7xpMULwdPaDJRVN6iw4XLeF2m11NT0cLlsxNucAGX+Vk5FbJBdzk7oTRnLiNRH7DFKFD+3ZEpyvZzoueloI4iDXtle4zNcuKRfifWziTMbAV7flM7/PVtHSM6gkbyOPfUXjoOGZeNq+/P7A9baFoOrDT90AM/9gzKCJ1uD8OHCNpJmSkjBanem6t/O96y6rXzPvI352PkdOYwSSG5R8CI08hlvIPIJpZwouoazJtfxK/Nv5yXrAWROI4TKe0YSUWQJvbaZSd46VwQhD+tdWKA9yUiELJHC4c4I8fqJuwBwfQmJDjmUddKnfww7ET9WRx/1RejgFLo55/uYgPR2P6fZ35Ao10yiAdbCzWFxF17XKUhlh5nIPzu1QGv0kMBzNzg8p7M6iQ1w1ToRjceqBS/R4+mEzzzRHVnsvr0MHLSmO6ZzS6W0xChFWBEhjjqRGh3iBLk8JvhclsANkDWWDVCmUia0lweQI/yysCCXhOnnXBMJrVXIb+6RybJAoUZnHP7q+mtxPRW5I32t6wGROKzlUQlt3PRfw/pBa1Xp5f6ikKh3AMAnmTys3r6pAULLqKkEw+rC8G9OY1pzXfIQrrYET0bLz5fjw+HIKlIKrcR9oWnGbK8g1BI7mCKTfjJ3AC2Z9TcWlvolb8aTHvRnMbOs5bQ1WbVTWrztgkHVSVCZ/ssOZTyQjhLNqrWyMktbXHQUAEtFZVOX5/nvMHcpWhCcgLTH1cMahvD2H7VuZpdB/1bfFh5KREDwcZhCqyYo3PPDpBEjExfZfQf2bTlk7HV9sLhkI0WUD4y7G344/U3h7AsPX9nsQ9J8CDo9QNvNj5yNWsjSqardOFk7XXteGnymI2hp0dDWX1FzKlnbbRocnT/PQKa93kUCixXgchXlsQ7nVqmOVqAfgEUFOr5WDR3f43lTmqUpooSbfVpfh07FN5qZ4mPJvIVwYRJE1tAiUBdZeWRc5h+O+vzPCtakjaXMFnIzn7jBvwSzRuXV/AcLYqPuYK3OeEnOkuVBN+1ybnhv+yAhr0wgkqcJEIfDwtiRHRdWKcMgGwNwuSpneZ0FRpCqfVWckLablkhrsFbBbzfsdkGb7UYYNwQIrBdwB+T2FYph9dr0edOqJfMAro+dBz9Q3VAgRcUoWJ0TdGTFJXnkW36OzjorgV/I78we+5EjP91540YlN56l1drljWkbLZL0KlLt7QZpcIagQY2FkY9Gi1cJJVxLZe7wKVXool2w6Qxy4hIRapvRfAAN0ejOBtCwH58uoYJnGNHshXn9eayKGMDSFcemgAPjJwoFKVAk6+ieaVwCgXLlirQ0gNbW0BNmis6c1BaRWjFKHginGmM/T6xJpTYWHlPCDL7r1rqeVnfpPbhzoLAOUnYg+6jNPiZRq+VqYLZYec3BRynch9eI8Lpo+nhSfBGaHz+D9VM2oIFv6SsM+Db/w7X523Y/kxE7Filg7mLf4nMnqo2JMS3RbDI6Ys5woPLi/TmJRdmGjZQG8M+U4qriw1/D9YlIg1hogZ+b75v5Xi24Oz04piqH8uhPKA/4ssFeEYseWQtDzKqfoaj4nbAI2t5sBR7ZSkgQbrQ6hrzJKBEzNA97vH01KSf892Siqj/NiDVjaMq72ZwslFqOyG2yEIqUPlt/y975SCl40iA/wIqHwzPLIosd+S76mmmea3uWeMyuPSzMIBFRQXYyq/y+y3rb5uX7eP56p48w1hWqSdm2D2OfvCjtB1LPfpQ02HYvLAX48GWhJ+m+jMSq7Je1IXPSVnOPOHSpbtQ1WrLcP0dKNUrhyJWrLr31TmrNMpOd4bRhINhXr/u9ouK/b5t4YD1rzWkGUJyrF7X9866GChwkJZCfE3KDfEdE92GPH9oMtJXK5tOBaI0V2IN6lgAvoWzQ3qidBycVzmOkiLaiJIp/0bu0+0KRnS3pwc1CSM5By+WGhd0LRUGZmA4mzmc5UfTAINvFqGUvmZ9AYj20qbPlM9MX2rjDTls8mz2ABfFSuCmXfWI9+39ziNWiwG6mxQy87gtMRG8yer5/OEg0OZQc+xR9A4N7FC2Fls48Z2LIMqNds+SSkEMCueVy2/dE6OsI5sNfcb1/N95zsoZmmOEouXu5B0uap59SsACIZrQKyqr3sc28Wil30VIbr+4bXYapDrUEVyKDVUi+sK0cx69T1XhW52X9y4wqvPv7eiT6eVQvlp28DCYlP8VkyOycszSssUlTz9aHphSFGs9DeK74ldJqAmUGyCCTKmPSMtkYwTHDO0EDMfVZrezWCs5MT99ii07PhLIPhSvEU6dp1MYHtlcbu/gbtjpmTy45oq4w1bbhIEiQocSMakxlOjVyycwYqFPc533HdKQ+Tgw2Cx42gt2aHc+dnUcKFJ4mBoqgiqDo2/QHvM+OZ/8It7N823t3godq0tHLZvngCicOwjLqdYr+emARL8/svNKRXgcDlieLuwyCSlDf4AYfQtIGkG7mhO/V/gFz7RjCmYBHylB3lUPCt01tQM89WmaIW9mQc99O7rlpHfP9Uvmvzrm3iRNKJ+jPhPbd/Ki3obfY2magNHYBdX2LYy9l1asoBQSmrdKH8sH2h2G6dCgorUc3CbsRGi5xQ/DYdMFwzjWCaq0ZyItDO44mcPN2ynENlpuqAgGnQc6mOHnKYK462GE5VNzvB2Jof4oMHWDsO7YsjKFIxaKz5Bu5LaP48d+DkI6p3e6QamFeQ0j+2/9wJA/aAhJ9SZSUZg3s33aMXCyO2ULSfK2eyVcHOO3pSZvmrQ/LOBtXWyqg2Q36vmbhYSLYYeE/5xRZENKK16aHMFE1nIW9d+owdGBp2twgoSVAoPJQxBnhWUMst/7sX8uSKE4Y9B9q1mf2dJUqnVm6bN+5IWwsgjqyD06Faxv6qx5Ixun9srk+KZt1v9zTa7inYXHHW0GUitY+3jhfUFTfYxo5+MHbQSnU+yGY+Wt0I7rP6UHZDIB570SUbUKwyYZC76kWMsq6NEL0ZYOZo5Dt26vGzEVXy1YfrPQgEvG6PX4vY1EFCvaqfnAxG5/cmHpjF5b/X9X3RgmB98+OpUMCpcAGV0LLJvuhVv6nAS7JyFJjo9y/mrjMLycpUeHdcwv8dnyh3z8BelWgEAMlpyVtAAR7jR9cohp1eDqwNvOZgjfO+UivkLIHHcBRYVymI3IHY1JCcTMBr9g2uhLuY8eiMllEpLL+i4BhKIdBLdADUyEyqC510ZBHq4coCxsb5DTDRBP2ENHcGmg2rNp+VL324DiH22X4L0B1QR/YQseXHQXJh9fyH3HG5V0jesxCHgn11gRf5qpdY1aqfGEWcsQaeJwESvDTlas4b5zSRoDydc5OCv4sv+nvI1Yw3Fosx/fEZpuC8cwkUtUq1E6piQZ3QJklJlmKJbAFRqRYFzVM3f/MEwb9jwZf63MTMAl0ca4jxI8PvuOIj46ZcImML28bb36yyUpnsSWQ9IQfNDsfbpsObORTH03dvCyTpFuyqstzSGj4d5Rppf/f9pAgfnhXot+NPMGs8Pmw89hQE/hgFR+m6VZzyPUnoWy5hQjE91FxB+Ap0AHqL5e3Ot0B+kUvybfyswuJioxP2+FzrPAdcTwg/OZ8JBQRplZT2Vl5pTUx/trXP0M/r448gk4yJxKNOpRfgbfn0G+rAwSi0EghcDcnS1zMVfcqsXPPu5693dBj7cK9hf0TRpwwE/YmMDxWkaU+oNUhz9mu+J90KmG62GHzq6lSLFDk6VPQ/GSjLeXg/4NX6WMu4Mx5IAq/zwxbOkGEvVEx9S1SSWFfE0etKp/XZVBnynb+jY+7jVYltCfsUCWMNDyqS3Gu9XwGneLDe7hAz53BA4hUtthrBk1yPUamQHU3PiEs7Rn7kqNbnWCesK1r+xRNLF0ioQqdwd+pvgaCNo5nvgWtHHXrWd8a2d9uhJDH7Fa/i4Oxua+faqdPstjUpx4I2gtlCCUHa6Mb7XUvnJm/JDiEYQUeCGuDaWsGxN0H5j5/UOwMiENZIpZiXUC+gqIGVND+7SpImYKWTZ4jzzAM6NyBcZlFGZVWW/hexnSxrOt/3OWvaeE9oeqn8FbWjmyAVtOb6Riv+SHRny4RaoYB/cUZ4N/J4nxRIxv+CVI2J6YPv23JCV52PigE8K1iEjow+dQCPw3/8Q+/ObXrAXdy/JmCTQIgEXxXc40jF6o06yRt9mFlm5EbXMrt58Yr02TWKK26rtlvuFehNpZNtX9MizYdTqITMWesOjdCqymZ7lNo2+Aw27YpmoI3ZbZ595OyhFolVEW+ONSrYOa4EiNIj/NsDm38Wxp/0T+fBsgTJiDYSCXGkvDR+CIGIK/M90l9MS+meDnpR46+QbKrozjUd1BDwHElohNjxUEN/XR/rUBgKAmF2SEO86c7hDpRrlieRqoqED+ra0Qb1kG5AA40PjmQY4IwK0qhGdrQiMhC3Qq6bFVVOE5IjfIGUNpzgHpGrWxgmUZ+3YpILXGqS1Oq1dElUO4SaQZc3jLxFlQxyf8jn/oMMudfCwRCmjUXYQIM+HPdBa/SubgYmmmtZ/cVd0jLSS/P0rDufe/CjHqfxnAunvK7NBKrPymEfNxnvt6l624IDJGOYFdlAk6uVpQDRQh9fGKeFDhR69QCLe00KjC2HlTkS1/SAz0k6fL3OjWxpVk08UCebpGtzETQZpI+Cy9S0fPVv3ivwDHuiFqZ7IvUVeNABBSdDY+j1Lu0qtiQp2mGsD0tbMq0K8rszoMSEWdnpfq1u0pqdIHjT35/1T0nYDfAEtapE4/fONSFlFy7asZiBLWTgn5U7oFBmYIN39NgSnXaZqktAV2YNe/fUDiCErRNgrpFvTnyBgufOfW48KBYY3a11dyqVeDEu28GFMYR8n73MNAQCIeXRm8CZSsjMpxx4pzDNkJ7L38TOTnRdeNvawxAzeWYMZGCHo2bjJxojm3WtRPeFqfdjJpe4wNQ+47JxK07CevixacYn5NPPyyRD920CFcfg/UAhfjPc37za0zJrMAskPlpbArLgyuHW0qi7kTTr+3ZBgfC1lXaZsqT5JbAn1OZrejaxjGdJ4WghlZWbKyofTWuJJYjkxDhHZDuCCi4ygDHEvprOsTIz9TngSwWnpDxXHHDprffRLE/Hem1+2GtBTZdL2FdE+Dq97TOV18PmuLPiTAwAc3WGHGXoUhtSX4TcHXarBe2ghxrCJfwfMwC3jb81HDNj0m5lQAr7kDx7Z8kJlDUWF6BeYheTZ159Zam3gKh6Y/HwI0qTjBexGDFPe+gjqym/L+y9iV810ddEYS9j9s5ROPejRl3X+y6swd5mnWOO+RNld17HpnCr6SyZXD4FkZ1MHiwp1aMBYU1aiQ0DFnNEfKbHx9wG1LCxy8za9YQzgF3nTx/H9Ot0cB0kEFrEDzj5RQiKYbnaLGfCv1YVCrNyBXSR822j9XD/1iQ1dPDmrQPsadfD3PYNSy+S5k1YsdEUff76jDRFMoUKFiWcz0Z2OOvBWLQzFO9kI178WjS8109YcfrXHyfq6D/18371H1htwFA/uk5RbWXaNxqhEUBGl4+gTRlJ4O9p0nCLeuLo/YsSvr/rMcnJYzCtAF8XlT6Dp+TWlWqU+FHvRWvKJ4ZEWpzMJ+8rhnT6AOuS6OKFuU+MEyKJ50Gn40z0lYlJkKiWT5Hc4ZjU5TCy67tjiBTi2SViJBrgk2Ne4ALUf2Ji8hbNKjGK7x7cS93U8PmOYAignRRPS2u74+FHXrftVm7WqdHO2HkYaEg2s/pw08VVpDmXXVFMVsrk1ohZnXmTxcQ+R62qJXwKqYLitWBRTi4lk8fDUs6YMIasqSlcLFOg1p9eLULmJXfzDP+E4mD0e2DgREgXa/AIdX4w67zu2d+VBxHnLuKD1AKbMCh9mYmnw0a9tHngLhe0Mq7Y6xegVuvkxlzhu36HvoZkGyxRrFqiispU3Mc1SqWbYlr8nmOjf3JnjhOsuX95wa/I4YCDC+MRVcXsrQww9A2C2O8UDGcchA305mDSOtJ6GAiQny+8EqGx1Pf7pdFcx2ZWQvg8nFCfshXA4SVCuCqjwzCZOzmt7ZpZufC3pEDKRIyooV3mRsD/NNgM3uTlktV8kKpjzONvMbEn+7ZGtrMZPR/NTigVJ9MvCDSNOGryFbpJMrp1p8va0KSkK6mLf2muhbCf0Tq++TBFHDb0A==\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode."}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_update","assistantMessageEvent":{"type":"text_end","contentIndex":1,"content":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode.","partial":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode.","textSignature":"{\"v\":1,\"id\":\"EEOz98jbfiJ3WKV86t03JJ3mV/T6r7BpoJkxtLy6tFSek86xtclg1YeWco/jcu9QmRz01Q8te3pZc3jpjZ/nkt0klh3XIm9LvCYw+rq0PMPK2MZ0dxrlja6O6AdUHKaDZIaqJCQvJHL3fhq0It/e/uZdbOPH0HlZhZ/3kwXP8lw2eto9+wUiDYjYXU4LrPjkSboCJDbm9NyBcyeFj6tEsTTNUUSwcennM5d82NnILjHoEdlqrwN9oZT4mYjGlH1O5fGaMH4TaICqWrM3rItMBHPpPbLbJ5amwIUbeB/xmAhxOQN9ItVyfNFeFqWUympGjAi1gzz7RdDgxUhmu1m2uQ8m+0S1SgYZr02oWUXvoH59uFA/eyGDchIGkg5C83IWDm5fUPBffzZdNUNFFbYuoE+I2ErN/Did\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}},"message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode.","textSignature":"{\"v\":1,\"id\":\"EEOz98jbfiJ3WKV86t03JJ3mV/T6r7BpoJkxtLy6tFSek86xtclg1YeWco/jcu9QmRz01Q8te3pZc3jpjZ/nkt0klh3XIm9LvCYw+rq0PMPK2MZ0dxrlja6O6AdUHKaDZIaqJCQvJHL3fhq0It/e/uZdbOPH0HlZhZ/3kwXP8lw2eto9+wUiDYjYXU4LrPjkSboCJDbm9NyBcyeFj6tEsTTNUUSwcennM5d82NnILjHoEdlqrwN9oZT4mYjGlH1O5fGaMH4TaICqWrM3rItMBHPpPbLbJ5amwIUbeB/xmAhxOQN9ItVyfNFeFqWUympGjAi1gzz7RdDgxUhmu1m2uQ8m+0S1SgYZr02oWUXvoH59uFA/eyGDchIGkg5C83IWDm5fUPBffzZdNUNFFbYuoE+I2ErN/Did\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"i81cZeHNPDObXdMZt8r3p5L43zh4JXhfxDXFceQCx1PeRv6TO2Ct3yDM+5phjpEIC33dbZ8MznIeoNwxdgcW1w1c/ie4saIqiIStbT0nEyiuUwkLQaI5tT2SeBoPW3zvzUD1T2O2ciD+rysMNcd3nWtdoK1MPfqfXdUM/q01yqcyFYgHNiFLm6a7zVuhEPrCfyFiHVQT7nj6CgBDe6cL84VosrlxWsqgsdl7wsZrWXRysfcSREANIpNzHts11+BBdV7QxwVZQXPAu3wn1V9ok3jeKTV5PuurwT47cJqk1613RrhjFnidy9yT7IYj/12VFDJGRGiw8VZz2Ymjg7S+9C5PGMhJBMNXNgkTZMJJ89jhzhwhekLAW4+VyFu9tGeuXdpW/Ntj4c3twpfHqIZ5nfxx8FO3qZX6sQ=="}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode.","textSignature":"{\"v\":1,\"id\":\"EEOz98jbfiJ3WKV86t03JJ3mV/T6r7BpoJkxtLy6tFSek86xtclg1YeWco/jcu9QmRz01Q8te3pZc3jpjZ/nkt0klh3XIm9LvCYw+rq0PMPK2MZ0dxrlja6O6AdUHKaDZIaqJCQvJHL3fhq0It/e/uZdbOPH0HlZhZ/3kwXP8lw2eto9+wUiDYjYXU4LrPjkSboCJDbm9NyBcyeFj6tEsTTNUUSwcennM5d82NnILjHoEdlqrwN9oZT4mYjGlH1O5fGaMH4TaICqWrM3rItMBHPpPbLbJ5amwIUbeB/xmAhxOQN9ItVyfNFeFqWUympGjAi1gzz7RdDgxUhmu1m2uQ8m+0S1SgYZr02oWUXvoH59uFA/eyGDchIGkg5C83IWDm5fUPBffzZdNUNFFbYuoE+I2ErN/Did\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":3111,"output":4187,"cacheRead":2560,"cacheWrite":0,"totalTokens":9858,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"Lk3p8vqABJCP6v5dULQh7JUTYuySS5bVRypiZy7QmCiJaYQinmNTiRD8TDfF3WGDuQIgOjCasioiN25HnbEijA0vAPv93A1wkOGGHYO8oy6mXeD0qpAjUPPTtlfjuasCyuVWSF11mqbj7dSqpyLgQi173eRP6eKoksNlCEXxSAQS4Fb08KTFVvg1TH43uoGSANcZkUpm0zuPv2bSoI+H13FePD3t6+JiTTulEb2PPaWs/G9LuxHMPxRw2+BykTc8tAmDfQOqPa5o6pyHSnE7kvRD8+ScxzyZNeMMhzMRdcBGvhSFuD4l4pEPcVkwMWyB1Bmbzt/e1Ge9XCzDNn2hq1/jU9LOFvlPqY2C58m4cILMYtIoq7UOU/IIqsGd59TLsQFvxE1/X19kpVz4ojb0TYhZHLcCg3A/4w=="}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode.","textSignature":"{\"v\":1,\"id\":\"EEOz98jbfiJ3WKV86t03JJ3mV/T6r7BpoJkxtLy6tFSek86xtclg1YeWco/jcu9QmRz01Q8te3pZc3jpjZ/nkt0klh3XIm9LvCYw+rq0PMPK2MZ0dxrlja6O6AdUHKaDZIaqJCQvJHL3fhq0It/e/uZdbOPH0HlZhZ/3kwXP8lw2eto9+wUiDYjYXU4LrPjkSboCJDbm9NyBcyeFj6tEsTTNUUSwcennM5d82NnILjHoEdlqrwN9oZT4mYjGlH1O5fGaMH4TaICqWrM3rItMBHPpPbLbJ5amwIUbeB/xmAhxOQN9ItVyfNFeFqWUympGjAi1gzz7RdDgxUhmu1m2uQ8m+0S1SgYZr02oWUXvoH59uFA/eyGDchIGkg5C83IWDm5fUPBffzZdNUNFFbYuoE+I2ErN/Did\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":3111,"output":4187,"cacheRead":2560,"cacheWrite":0,"totalTokens":9858,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"Lk3p8vqABJCP6v5dULQh7JUTYuySS5bVRypiZy7QmCiJaYQinmNTiRD8TDfF3WGDuQIgOjCasioiN25HnbEijA0vAPv93A1wkOGGHYO8oy6mXeD0qpAjUPPTtlfjuasCyuVWSF11mqbj7dSqpyLgQi173eRP6eKoksNlCEXxSAQS4Fb08KTFVvg1TH43uoGSANcZkUpm0zuPv2bSoI+H13FePD3t6+JiTTulEb2PPaWs/G9LuxHMPxRw2+BykTc8tAmDfQOqPa5o6pyHSnE7kvRD8+ScxzyZNeMMhzMRdcBGvhSFuD4l4pEPcVkwMWyB1Bmbzt/e1Ge9XCzDNn2hq1/jU9LOFvlPqY2C58m4cILMYtIoq7UOU/IIqsGd59TLsQFvxE1/X19kpVz4ojb0TYhZHLcCg3A/4w=="},"toolResults":[]}
{"type":"agent_end","messages":[{"role":"user","content":[{"type":"text","text":"IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ..."}],"timestamp":1775941589168},{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"14+OHuNzbVtWrrl4kGGqOWcoHgiYfcmhjMZ0dAV4SPzYxyW8PSHvIwNAMzS27TXmTh9aXiUqELk61H6iaOnC/k6WDbVX4Z2oB7EXMzP7wuQWTt+CprzEilHcRzcshjqAfzZX5e+hTE4DZWbkzkOulFbhJ9OOiWGuIle+E/6IkB7UwV8HcnG9WZt2eyHgU+TtnXCBgrXKz/NbX1IFO+brDmBm5A38ibfXUry9NQOaWKYsE6auxQFBlG+kQVE+ds3Tex8G+Bbiebbp+s4E6hFHq2pWLFqY9kFXb/0WoCrO5+D7DdsHN5LL6/LE3aYjIeJU7bs6tSpy8csw8RJGKt65UKBDcnEU5eWMStcK48GnTAql5m0mrwzP4txaNHPz6SLSYJPi2ACNgAFAfwu7fBbkpQzp7zYWXGQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","name":"bash","arguments":{"command":"ls -la"},"partialJson":"{\"command\":\"ls -la\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":109,"output":572,"cacheRead":2432,"cacheWrite":0,"totalTokens":3113,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941589217,"responseId":"29CITj0nrTvaiQ1tW5mTfgaec3iZjO0ko6z/A6hdhU1Cv3Ni8pN4nNcS39UUDoSwYvGR9l3AeBhL3fxBEsty+ZnthMxBGP83mm1U7rnz9UP/9dUhpJJrBiSBZLJX0EkZR9R5wW0CGrk3VYswkGvu1YPbpBBeYJQ4Y4ASGKEmdKWlzFfExN/4LsrRKYTrqnJPu06js3L2DqYoMKZKhSWh0RoGiv7jOINGVIEVHuQCAb9YC49UWlafPKf2dAblnA58c60jlXqC4lA9YXpVr7Jc3NMrWyZQy5gxoelWl3SmuLJrxKJjfIVee9Q5TKr8ISq8FTHblFIp0/W3P3B2kcZXTgAMpWi2olgPneOvhAP8+99pzoRz0IHmzI+4qidvwB/jNIJIqSKZZfgeMaHz1/AATDZgaV9FBzMw0g=="},{"role":"toolResult","toolCallId":"call_VgwWgBXQkVGqJUdsmRY5ibXz|wY0+xEV8alQPLRs/hWNoHslnA4Yq3BtUKpVuX9aICmX1MUdI+cHyqURTN5bfiBnA3iQxqefvaSK8JllmcyX4UyibaWbdD1x9ZiHXSeaa/OjsWK/TPwi3P8Xl0N48ABFwrLT8Y4FfXe+KXAnkRbhzMxJFjIQ3vcnegG1HQJSPHSFJ+Gl2ZvdJLFTpbDFoTiJFdMBB+6Q3aZ9OBntr6SraCQyf8Jrn1KXToK2Wjtg6tanj1NPRRKkNzJ3AwlqicGcOxVV/iDG7CwALqLrIMSrWJBm+p5sTCeQNwAMGyk1WUv5TVGhO+Tx8o5aH8Lc87sd0feSP9TWExWmEL3IL7OMKAw9pPBaALtfX8iKuSCBoeypYTcjaVauBa6hDhglHo5PyZ00saeEmFFZE7Jit1yXjmRbDKzPdct8=","toolName":"bash","content":[{"type":"text","text":"total 8\ndrwxr-xr-x 1 alex alex  368 Apr 11 22:00 .\ndrwxr-xr-x 1 alex alex  122 Apr 11 17:42 ..\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 adapt\n-rw-r--r-- 1 alex alex 1090 Apr 11 22:00 AGENTS.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 animate\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 arrange\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 audit\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 bolder\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 clarify\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 colorize\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 critique\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 delight\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 distill\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 extract\ndrwxr-xr-x 1 alex alex   34 Apr  9 11:27 frontend-design\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 harden\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 normalize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 onboard\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 optimize\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 overdrive\ndrwxr-xr-x 1 alex alex   56 Apr 11 21:56 .pi\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 polish\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 quieter\n-rw-r--r-- 1 alex alex 3664 Apr 11 22:04 SKILL.md\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 teach-impeccable\ndrwxr-xr-x 1 alex alex   16 Apr  9 11:27 typeset\n"}],"isError":false,"timestamp":1775941609568},{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"yeXJ6s63iuUndsk5MHjdQBt54VLjpL2HtLsElYO1T6MfIngwLTmzWN0z8ELtlcw3LK4ovCJvl2AjM7uhhxHth3KvcjG2ZhHMbt+KqzLi/Bgwlss7GkcKTjKzrH9+m80WNAQBfTYJwI46vodmGSJG5ZQCmPusJ3pr9QcLNwcjSPlrAFY4ObVOZdJNlZnhurAiWXD+0Zggvf9GWuicCqXip3wPkcEU3AOVxj0qI5QuTuVyPUy6t4KGy5svAQKiye2ylk4u4MTzJhrrsytr29PWYRXDisDwuLIpeOAAR79FV7s5VlHplGECVh6XozHx14Ssn2qUNcgJ+tbtAFUGebHr5I4ijtBbnv9W4L9UsUdzouEaS2RIwV+9Yk0R0BUlXs1dkPY/oL7ZHdbEReeV3knNI1VI/btDaVU=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","name":"read","arguments":{"path":"SKILL.md"},"partialJson":"{\"path\":\"SKILL.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":1397,"output":456,"cacheRead":2432,"cacheWrite":0,"totalTokens":4285,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941609573,"responseId":"DAavDSBAP1TFdtcwYxwuLKIE7bLxUKoOcxxUeljfA+gF+oV7bzBAfOk7YdbQqeiSBFrHJznJATEqLmt4YszSOqT6glHJSieds1Jy9UVm3dLfWijxSCsR5FGwn/ueeotrAcWa4jDaJyRgx5VAjws88h6IYx3ZEUjl73oopuWmw5nudoYvGZoIco6eN4nA19yGCfX+URtCIbqPmhgP+Vj4XqXmTkauucj0ODDwghvga9uLBvys8LrSYI7ztoY0IKJ5g7YrImSRUubRa8DC1pjVLP5Vop35dkkL+ltSBRFJEljTCb0UKX5zRwdFw5rZmJbGPXCtP7yqN+5CmNDGPz3yELU6mw4sDslkusOr8GgflnOM8o8KMIhCZAZYTMiuqwVA+JwAOg0cvsc3KSJSSSA1VRlK3ib2peLhhg=="},{"role":"toolResult","toolCallId":"call_J8tGrukVvpTKRZpju7zTF44s|Zh4ViPQXpyisOk34xLj5QzBfEE3xuVMtARCMpwEUrK5FERPZOU2e+YgxG4ERaTbfkaYO2tvtl0hPYSSNS7DA4NslBMCqYEUibLdE6+cuxQDAQBFDQtq+lGGfxsB/X8/zAdBqopohbdSOxW8niwBHFUB2fQRPx4BhCi4LfQy/3XMsPUu4yKV6opjIuQDMkbPiu7FsWXf0tQtE67I4XyQuvP42gcVox2tlCrC5/8V18oJCSBGHfCrVDo+dbwimBOYi2fckmxHCbn6gvrs3Irt7v5MFxak2rtG3EgCtVuLgQgB/0pFwLNgt2e2JZVx/9JZp4ms0jHVsOVOBaRK5i+iib3sTYFrqLESUVuU1ze8toP8CIIBWDL3HgJLMucj48YoCpChnYYb6oXLVa8QVNY9hrSHdk5fSma4=","toolName":"read","content":[{"type":"text","text":"---\nname: frontend\ndescription: Use when a task touches frontend UI/UX/design quality and the agent needs to choose which specialized frontend skill or combination of skills to load from this frontend skill pack.\n---\n\n# Frontend Skill Router\n\nPick the smallest set that matches the job.\n\n## First checks\n\n1. **Net-new UI or major visual direction work** → use `frontend-design`.\n2. **No design context yet** and chosen skill says to invoke `frontend-design` → run `teach-impeccable` first if instructions and `.impeccable.md` do not already contain design context.\n3. **If a chosen skill requires `frontend-design`, load it first. Do not skip it. Do not place it later in the sequence.**\n4. **If a skill's own doc has mandatory prep, follow it.**\n\nSkills that must route through `frontend-design`: `adapt`, `animate`, `arrange`, `audit`, `bolder`, `clarify`, `colorize`, `critique`, `delight`, `distill`, `normalize`, `onboard`, `overdrive`, `polish`, `quieter`, `typeset`.\n\n## Choose by primary need\n\n| Need | Skill |\n|---|---|\n| Build or redesign distinctive UI | `frontend-design` |\n| Gather persistent design context once | `teach-impeccable` |\n| Review UX/design quality | `critique` |\n| Review technical UI quality: a11y, perf, theming, responsive | `audit` |\n| Fix layout, spacing, hierarchy, composition | `arrange` |\n| Improve typography and readability | `typeset` |\n| Simplify, declutter, remove noise | `distill` |\n| Tone down intensity without removing quality | `quieter` |\n| Add color, warmth, palette energy | `colorize` |\n| Make safe/bland UI more striking | `bolder` |\n| Add joy, charm, personality | `delight` |\n| Add purposeful motion and micro-interactions | `animate` |\n| Push into technically ambitious wow-factor | `overdrive` |\n| Improve onboarding, empty states, first-run flow | `onboard` |\n| Fix labels, errors, helper text, instructions | `clarify` |\n| Adapt for mobile, breakpoints, devices, contexts | `adapt` |\n| Fix speed, jank, rendering, bundle/image cost | `optimize` |\n| Fix resilience: errors, overflow, i18n, bad data | `harden` |\n| Bring drifted UI back to system standards | `normalize` |\n| Extract reusable components/tokens/patterns | `extract` |\n| Final fit-and-finish before ship | `polish` |\n\n## Common confusions\n\n- `critique` vs `audit` → design judgment vs measurable implementation quality.\n- `arrange` vs `polish` → structural layout pass vs final detail pass.\n- `distill` vs `quieter` → remove complexity vs reduce visual intensity.\n- `delight` vs `animate` → personality/joy vs motion mechanics.\n- `normalize` vs `extract` → align to existing system vs create shared system assets.\n- `bolder` vs `colorize` → stronger overall impact vs specifically more chroma.\n- `optimize` vs `harden` → speed/smoothness vs resilience/edge cases.\n\n## Common combos\n\n- New feature: `frontend-design` → specialist skill(s) → `polish`\n- UX + technical review: `frontend-design` → `critique` + `audit`\n- Busy screen cleanup: `frontend-design` → `distill` + `arrange`, add `quieter` if still loud\n- Repeated patterns + token drift: `extract` + `normalize`\n- First-run experience: `frontend-design` → `onboard`, add `clarify`, `delight`, or `polish` only if explicitly needed\n\n## Routing discipline\n\n- Choose **1 primary skill** from the user's explicit ask.\n- Add specialists only for clearly stated extra concerns or mandatory prep.\n- Do **not** add speculative helpers just because they might help.\n- `audit` is for review/check requests, not default build or refactor work.\n- `polish` is for explicit final-pass or finishing-touch requests.\n- `typeset` is for explicit typography/readability issues.\n"}],"isError":false,"timestamp":1775941622780},{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"MPasRfpWK2mWwH/Ug2Yeql8DX3Avguk6QSOcq40WV1OcHoeq8FH/If9ETqvEKHfm6L2AwWbCa6TfZae22iTEZEtRryy12gcO97RFUJ+El6pHwkYNBNvGXpk6a5YJXpt/zEM/ElvSHV2hw/osq+l0X0OLgS6aI+HjleAT7pSbRAUelJcPIGFHDTlmaLVw2e02bYnSzHMIE+0gKtqDBCECr2qKs4R7rS5weQ/DLY0yuwOB+yEWWnJB40PheZHaVHZWi8VQgShq3T+8YqN0n/QHSgSFId50E+CjBdVYpQr61YY/GdUtWymkPz5k08TJYmRlVfcJGv23oBSz+ys6dGhYw1UHjXzA+M9MjuQOurybSymA3W05u2fQ7uXwJwYHmRQ1auxVb7oDX91R9X4zTdOZrjFgPvQrZwQ=\",\"summary\":[],\"type\":\"reasoning\"}"},{"type":"toolCall","id":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","name":"read","arguments":{"path":".impeccable.md"},"partialJson":"{\"path\":\".impeccable.md\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":2925,"output":223,"cacheRead":2432,"cacheWrite":0,"totalTokens":5580,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941622783,"responseId":"oQqNWWOkCxhoIjbseRwz8DTrMD+V3llJ2p8/FiOQbONl9Url3WMlQ3o8pv38AAqbe/HOKnSPDysoFYY0LIFoEAZG6t+bYdaA4UAgfW+yo75c9I1uOfrOGyYkcPV+qg8mWy+/HIK8wMq5H31dXWjPMs9S6iFg0inXsT5jUa/vWKEO1m7JoRjNRwphqkLrdHzI5kwGsaEDUjFHrpRVy8N4Q3Ig1HrexoGMOnL7M8Obr5ldTttwbcBK2TGc4joHM6iWxWt6CU2eirx+0eK2LNNHIferm2vNuJqM3SERT2hNfBJ+iaRpZM+HbHsBwsAtv8MiXWqVCqnqZaWRRlkbsqD0iEAwUlmdgfj4cOwixFnAMdmoKgpO2gqNXayJpxM9zEv9VQBu1TckL+cmR5q5Vy5lp6QZP9s6FgtlCw=="},{"role":"toolResult","toolCallId":"call_ArW5F6YCKKL2zvBkPgYUuRc6|tdGbsXNWMT6nXILqWn4AHenuaTpNBzHN9qpbS0ir/Q/zc6VXLIi67w3eCtOOXAifF2Kx/jCHT071BOHm8yYvlg66dbCcp0vekx8pbSxF2g2ojdw5ePG0u5PgQXCVUoHe2o4rWzaEhuH/pKVIfffTcPozN/ADc18NKTxvN/5BZ/uf4xumIHelrhp2N358pzcrOcOwxqNnkd/JSH4xyoeWqm4lbjooA1Y88UYNtzPDyG7FkZ5WC25obz/CNj47rvkhloRyTKIwBLh835vSQhJ9qvx9kSqPh/U4Sqy2w9g5DSnygbjWEHMpCx4UmasxPepJgWG/fZDapT4Rz7ZZdU8YspStXY+w/2tSlknewEU7gXlDdO7X3nC+Kaen/8n+MYoHghiwdgf66o4NTxZCtPzuC33Y7nzU+qY=","toolName":"read","content":[{"type":"text","text":"ENOENT: no such file or directory, access '/home/alex/.pi/agent/skills/frontend/.impeccable.md'"}],"details":{},"isError":true,"timestamp":1775941631009},{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning Skill Execution**\n\nI need to remember to always load \"caveman\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\n\n**Determining Skill Load Order**\n\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\n\n**Deciding Skill Loading Order**\n\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\n\n**Organizing Skill Load Sequence**\n\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\n\n**Crafting Skills Output**\n\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\n\n**Constructing Final Response**\n\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).","thinkingSignature":"{\"encrypted_content\":\"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\",\"id\":\"rOFTZp/zbT7GDrCtCFBibn3OgBc6ftA3H6nqlu9qPWP/IispvUxMhS3zL6ZvZAOPb4mOrWSNPFJFHlyabt1e2cCXm1hnGHTOLQUXzYDcgBirYrVtux4usOdaULNrbsR3KkPK5EcqFT+cEyLdhYJY77ameG0IxsUQ557239xR97nCOxzSrTNEQR2Nf/HTEDWdQnUSltm9EAIYBHVUxnSUtvKmkrHYtFDpps4PHcTeoLRkmbiHZFFGxzmyidwyJQV13WNK271XnU1zxwRs/qBRF4TXGeSSb8N2uZmvoItS2CkOeY/dRcKhwau6S1h3LVkGhOmy72pl0gSSARVH+A/N3H4crK2DY8A9hPQ8qYt02XR+/aSqpj4tIrHt92aDP7Ia8nzikBzgVTWi3TtyFi3wmrmHC8wvKto=\",\"summary\":[{\"text\":\"**Planning Skill Execution**\\n\\nI need to remember to always load \\\"caveman\\\" in the Skills list. The user clarified they want to use the question tool for decisions, but their specific request doesn’t need further clarification. I also need to check SKILL.md: if 'frontend-design' is necessary, I should first run 'teach-impeccable' since it's missing design context. Afterward, I'll load 'frontend-design,' followed by 'onboard,' and ensure to include 'delight' and 'polish' as the user explicitly requested those features.\",\"type\":\"summary_text\"},{\"text\":\"**Determining Skill Load Order**\\n\\nI’m adding both skills since the user specifically requested characteristics matched by them. The plan is to set the order with 'teach-impeccable' first, followed by 'frontend-design.' The 'MUST DO' guidelines say that I should always load the 'caveman' skill, but it's not necessarily first. However, 'frontend-design' must come before other skills if it’s required. So, I'll ensure 'teach-impeccable' loads first, followed by 'frontend-design,' and then include 'caveman' at an appropriate time.\",\"type\":\"summary_text\"},{\"text\":\"**Deciding Skill Loading Order**\\n\\nWhile it's not mandatory to put 'caveman' first, it's wiser to load 'teach-impeccable' first because the .impeccable.md is missing. After that, the loading order should go 'frontend-design,' followed by 'onboard,' 'delight,' and 'polish.' Since 'caveman' is a meta-skill, I might include it at the start or the end, as the guidelines say to always load it but don’t specify its position. So, the order should be: teach-impeccable, frontend-design, onboard, delight, and polish.\",\"type\":\"summary_text\"},{\"text\":\"**Organizing Skill Load Sequence**\\n\\nI need to make sure all the appropriate skills are loaded. Since 'caveman' is a general skill, I might include it at the front. However, the 'frontend SKILL Router' suggests the sequence should start with 'teach-impeccable,' followed by 'frontend-design,' and so on. Including 'caveman' first doesn’t seem to conflict with the guidelines. For clarity, I could outline the order as: teach-impeccable, frontend-design, onboard, delight, polish, and then caveman overall.\",\"type\":\"summary_text\"},{\"text\":\"**Crafting Skills Output**\\n\\nSkills: teach-impeccable, frontend-design, onboard, delight, polish, caveman  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seed design context), frontend-design (visual system), onboard (first-run flows), delight (personality), polish (finish), caveman (brief-mode)\",\"type\":\"summary_text\"},{\"text\":\"**Constructing Final Response**\\n\\nSkills: caveman, teach-impeccable, frontend-design, onboard, delight, polish  \\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish  \\nWhy: teach-impeccable (seeds design context), frontend-design (sets visual direction), onboard (builds first-run flow), delight (adds personality to avoid generic AI UI), polish (provides final fit-and-finish), caveman (ensures concise mode).\",\"type\":\"summary_text\"}],\"type\":\"reasoning\"}"},{"type":"text","text":"Skills: caveman, teach-impeccable, frontend-design, onboard, delight, polish\nOrder: caveman → teach-impeccable → frontend-design → onboard → delight → polish\nWhy: teach-impeccable seeds missing design context; frontend-design defines distinctive visual direction; onboard builds the first-run flow; delight injects non-generic personality; polish finishes details; caveman = brief mode.","textSignature":"{\"v\":1,\"id\":\"EEOz98jbfiJ3WKV86t03JJ3mV/T6r7BpoJkxtLy6tFSek86xtclg1YeWco/jcu9QmRz01Q8te3pZc3jpjZ/nkt0klh3XIm9LvCYw+rq0PMPK2MZ0dxrlja6O6AdUHKaDZIaqJCQvJHL3fhq0It/e/uZdbOPH0HlZhZ/3kwXP8lw2eto9+wUiDYjYXU4LrPjkSboCJDbm9NyBcyeFj6tEsTTNUUSwcennM5d82NnILjHoEdlqrwN9oZT4mYjGlH1O5fGaMH4TaICqWrM3rItMBHPpPbLbJ5amwIUbeB/xmAhxOQN9ItVyfNFeFqWUympGjAi1gzz7RdDgxUhmu1m2uQ8m+0S1SgYZr02oWUXvoH59uFA/eyGDchIGkg5C83IWDm5fUPBffzZdNUNFFbYuoE+I2ErN/Did\"}"}],"api":"openai-responses","provider":"github-copilot","model":"gpt-5-mini","usage":{"input":3111,"output":4187,"cacheRead":2560,"cacheWrite":0,"totalTokens":9858,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941631013,"responseId":"Lk3p8vqABJCP6v5dULQh7JUTYuySS5bVRypiZy7QmCiJaYQinmNTiRD8TDfF3WGDuQIgOjCasioiN25HnbEijA0vAPv93A1wkOGGHYO8oy6mXeD0qpAjUPPTtlfjuasCyuVWSF11mqbj7dSqpyLgQi173eRP6eKoksNlCEXxSAQS4Fb08KTFVvg1TH43uoGSANcZkUpm0zuPv2bSoI+H13FePD3t6+JiTTulEb2PPaWs/G9LuxHMPxRw2+BykTc8tAmDfQOqPa5o6pyHSnE7kvRD8+ScxzyZNeMMhzMRdcBGvhSFuD4l4pEPcVkwMWyB1Bmbzt/e1Ge9XCzDNn2hq1/jU9LOFvlPqY2C58m4cILMYtIoq7UOU/IIqsGd59TLsQFvxE1/X19kpVz4ojb0TYhZHLcCg3A/4w=="}]}