pi/pi-skills
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
1f0df3ed0ddf668b19372270ff2a67260928e2a8
pi-skills/frontend/.pi/subagents/runs/f06bdc52-32d7-4bbb-9702-04c92994f91f/stdout.log
alex wiesner 1f0df3ed0d changes
2026-04-11 23:16:38 +01:00

144 lines
231 KiB
Plaintext
Raw Blame History

{"type":"session","version":3,"id":"71daf6a3-ca60-430d-bfa7-8426b5759ff7","timestamp":"2026-04-11T20:59:39.792Z","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. Inspect the skill folders if needed. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ..."}],"timestamp":1775941180130}}
{"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. Inspect the skill folders if needed. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ..."}],"timestamp":1775941180130}}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"command","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":"{\"command"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{},"partialArgs":"{\"command"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\":\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":""},"partialArgs":"{\"command\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":""},"partialArgs":"{\"command\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"ls","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls"},"partialArgs":"{\"command\":\"ls"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls"},"partialArgs":"{\"command\":\"ls"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":" -","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -"},"partialArgs":"{\"command\":\"ls -"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -"},"partialArgs":"{\"command\":\"ls -"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"1","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"},"partialArgs":"{\"command\":\"ls -1"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"},"partialArgs":"{\"command\":\"ls -1"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"},"partialArgs":"{\"command\":\"ls -1\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"},"partialArgs":"{\"command\":\"ls -1\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":0,"toolCall":{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"}},"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":86,"output":17,"cacheRead":2176,"cacheWrite":0,"totalTokens":2279,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":86,"output":17,"cacheRead":2176,"cacheWrite":0,"totalTokens":2279,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":86,"output":17,"cacheRead":2176,"cacheWrite":0,"totalTokens":2279,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"}}
{"type":"tool_execution_start","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","args":{"command":"ls -1"}}
{"type":"tool_execution_update","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","args":{"command":"ls -1"},"partialResult":{"content":[]}}
{"type":"tool_execution_update","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","args":{"command":"ls -1"},"partialResult":{"content":[{"type":"text","text":"adapt\nanimate\narrange\naudit\nbolder\nclarify\ncolorize\ncritique\ndelight\ndistill\nextract\nfrontend-design\nharden\nnormalize\nonboard\noptimize\noverdrive\npolish\nquieter\nteach-impeccable\ntypeset\n"}],"details":{}}}
{"type":"tool_execution_end","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","result":{"content":[{"type":"text","text":"adapt\nanimate\narrange\naudit\nbolder\nclarify\ncolorize\ncritique\ndelight\ndistill\nextract\nfrontend-design\nharden\nnormalize\nonboard\noptimize\noverdrive\npolish\nquieter\nteach-impeccable\ntypeset\n"}]},"isError":false}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","content":[{"type":"text","text":"adapt\nanimate\narrange\naudit\nbolder\nclarify\ncolorize\ncritique\ndelight\ndistill\nextract\nfrontend-design\nharden\nnormalize\nonboard\noptimize\noverdrive\npolish\nquieter\nteach-impeccable\ntypeset\n"}],"isError":false,"timestamp":1775941181609}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","content":[{"type":"text","text":"adapt\nanimate\narrange\naudit\nbolder\nclarify\ncolorize\ncritique\ndelight\ndistill\nextract\nfrontend-design\nharden\nnormalize\nonboard\noptimize\noverdrive\npolish\nquieter\nteach-impeccable\ntypeset\n"}],"isError":false,"timestamp":1775941181609}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":86,"output":17,"cacheRead":2176,"cacheWrite":0,"totalTokens":2279,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"},"toolResults":[{"role":"toolResult","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","content":[{"type":"text","text":"adapt\nanimate\narrange\naudit\nbolder\nclarify\ncolorize\ncritique\ndelight\ndistill\nextract\nfrontend-design\nharden\nnormalize\nonboard\noptimize\noverdrive\npolish\nquieter\nteach-impeccable\ntypeset\n"}],"isError":false,"timestamp":1775941181609}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"path","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":"{\"path"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{},"partialArgs":"{\"path"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\":\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":""},"partialArgs":"{\"path\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":""},"partialArgs":"{\"path\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"extract","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract"},"partialArgs":"{\"path\":\"extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract"},"partialArgs":"{\"path\":\"extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"/S","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/S"},"partialArgs":"{\"path\":\"extract/S"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/S"},"partialArgs":"{\"path\":\"extract/S"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"K","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SK"},"partialArgs":"{\"path\":\"extract/SK"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SK"},"partialArgs":"{\"path\":\"extract/SK"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"ILL","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL"},"partialArgs":"{\"path\":\"extract/SKILL"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL"},"partialArgs":"{\"path\":\"extract/SKILL"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":".md","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"},"partialArgs":"{\"path\":\"extract/SKILL.md"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"},"partialArgs":"{\"path\":\"extract/SKILL.md"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"},"partialArgs":"{\"path\":\"extract/SKILL.md\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"},"partialArgs":"{\"path\":\"extract/SKILL.md\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":0,"toolCall":{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"}},"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":170,"output":18,"cacheRead":2176,"cacheWrite":0,"totalTokens":2364,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":170,"output":18,"cacheRead":2176,"cacheWrite":0,"totalTokens":2364,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":170,"output":18,"cacheRead":2176,"cacheWrite":0,"totalTokens":2364,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"}}
{"type":"tool_execution_start","toolCallId":"call_QyRuYwIQ8eef9WIYrGSc2iid","toolName":"read","args":{"path":"extract/SKILL.md"}}
{"type":"tool_execution_end","toolCallId":"call_QyRuYwIQ8eef9WIYrGSc2iid","toolName":"read","result":{"content":[{"type":"text","text":"---\nname: extract\ndescription: Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.\n---\n\nIdentify reusable patterns, components, and design tokens, then extract and consolidate them into the design system for systematic reuse.\n\n## Discover\n\nAnalyze the target area to identify extraction opportunities:\n\n1. **Find the design system**: Locate your design system, component library, or shared UI directory (grep for \"design system\", \"ui\", \"components\", etc.). Understand its structure:\n - Component organization and naming conventions\n - Design token structure (if any)\n - Documentation patterns\n - Import/export conventions\n \n **CRITICAL**: If no design system exists, ask before creating one. Understand the preferred location and structure first.\n\n2. **Identify patterns**: Look for:\n - **Repeated components**: Similar UI patterns used multiple times (buttons, cards, inputs, etc.)\n - **Hard-coded values**: Colors, spacing, typography, shadows that should be tokens\n - **Inconsistent variations**: Multiple implementations of the same concept (3 different button styles)\n - **Reusable patterns**: Layout patterns, composition patterns, interaction patterns worth systematizing\n\n3. **Assess value**: Not everything should be extracted. Consider:\n - Is this used 3+ times, or likely to be reused?\n - Would systematizing this improve consistency?\n - Is this a general pattern or context-specific?\n - What's the maintenance cost vs benefit?\n\n## Plan Extraction\n\nCreate a systematic extraction plan:\n\n- **Components to extract**: Which UI elements become reusable components?\n- **Tokens to create**: Which hard-coded values become design tokens?\n- **Variants to support**: What variations does each component need?\n- **Naming conventions**: Component names, token names, prop names that match existing patterns\n- **Migration path**: How to refactor existing uses to consume the new shared versions\n\n**IMPORTANT**: Design systems grow incrementally. Extract what's clearly reusable now, not everything that might someday be reusable.\n\n## Extract & Enrich\n\nBuild improved, reusable versions:\n\n- **Components**: Create well-designed components with:\n - Clear props API with sensible defaults\n - Proper variants for different use cases\n - Accessibility built in (ARIA, keyboard navigation, focus management)\n - Documentation and usage examples\n \n- **Design tokens**: Create tokens with:\n - Clear naming (primitive vs semantic)\n - Proper hierarchy and organization\n - Documentation of when to use each token\n \n- **Patterns**: Document patterns with:\n - When to use this pattern\n - Code examples\n - Variations and combinations\n\n**NEVER**:\n- Extract one-off, context-specific implementations without generalization\n- Create components so generic they're useless\n- Extract without considering existing design system conventions\n- Skip proper TypeScript types or prop documentation\n- Create tokens for every single value (tokens should have semantic meaning)\n\n## Migrate\n\nReplace existing uses with the new shared versions:\n\n- **Find all instances**: Search for the patterns you've extracted\n- **Replace systematically**: Update each use to consume the shared version\n- **Test thoroughly**: Ensure visual and functional parity\n- **Delete dead code**: Remove the old implementations\n\n## Document\n\nUpdate design system documentation:\n\n- Add new components to the component library\n- Document token usage and values\n- Add examples and guidelines\n- Update any Storybook or component catalog\n\nRemember: A good design system is a living system. Extract patterns as they emerge, enrich them thoughtfully, and maintain them consistently."}]},"isError":false}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_QyRuYwIQ8eef9WIYrGSc2iid","toolName":"read","content":[{"type":"text","text":"---\nname: extract\ndescription: Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.\n---\n\nIdentify reusable patterns, components, and design tokens, then extract and consolidate them into the design system for systematic reuse.\n\n## Discover\n\nAnalyze the target area to identify extraction opportunities:\n\n1. **Find the design system**: Locate your design system, component library, or shared UI directory (grep for \"design system\", \"ui\", \"components\", etc.). Understand its structure:\n - Component organization and naming conventions\n - Design token structure (if any)\n - Documentation patterns\n - Import/export conventions\n \n **CRITICAL**: If no design system exists, ask before creating one. Understand the preferred location and structure first.\n\n2. **Identify patterns**: Look for:\n - **Repeated components**: Similar UI patterns used multiple times (buttons, cards, inputs, etc.)\n - **Hard-coded values**: Colors, spacing, typography, shadows that should be tokens\n - **Inconsistent variations**: Multiple implementations of the same concept (3 different button styles)\n - **Reusable patterns**: Layout patterns, composition patterns, interaction patterns worth systematizing\n\n3. **Assess value**: Not everything should be extracted. Consider:\n - Is this used 3+ times, or likely to be reused?\n - Would systematizing this improve consistency?\n - Is this a general pattern or context-specific?\n - What's the maintenance cost vs benefit?\n\n## Plan Extraction\n\nCreate a systematic extraction plan:\n\n- **Components to extract**: Which UI elements become reusable components?\n- **Tokens to create**: Which hard-coded values become design tokens?\n- **Variants to support**: What variations does each component need?\n- **Naming conventions**: Component names, token names, prop names that match existing patterns\n- **Migration path**: How to refactor existing uses to consume the new shared versions\n\n**IMPORTANT**: Design systems grow incrementally. Extract what's clearly reusable now, not everything that might someday be reusable.\n\n## Extract & Enrich\n\nBuild improved, reusable versions:\n\n- **Components**: Create well-designed components with:\n - Clear props API with sensible defaults\n - Proper variants for different use cases\n - Accessibility built in (ARIA, keyboard navigation, focus management)\n - Documentation and usage examples\n \n- **Design tokens**: Create tokens with:\n - Clear naming (primitive vs semantic)\n - Proper hierarchy and organization\n - Documentation of when to use each token\n \n- **Patterns**: Document patterns with:\n - When to use this pattern\n - Code examples\n - Variations and combinations\n\n**NEVER**:\n- Extract one-off, context-specific implementations without generalization\n- Create components so generic they're useless\n- Extract without considering existing design system conventions\n- Skip proper TypeScript types or prop documentation\n- Create tokens for every single value (tokens should have semantic meaning)\n\n## Migrate\n\nReplace existing uses with the new shared versions:\n\n- **Find all instances**: Search for the patterns you've extracted\n- **Replace systematically**: Update each use to consume the shared version\n- **Test thoroughly**: Ensure visual and functional parity\n- **Delete dead code**: Remove the old implementations\n\n## Document\n\nUpdate design system documentation:\n\n- Add new components to the component library\n- Document token usage and values\n- Add examples and guidelines\n- Update any Storybook or component catalog\n\nRemember: A good design system is a living system. Extract patterns as they emerge, enrich them thoughtfully, and maintain them consistently."}],"isError":false,"timestamp":1775941182726}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_QyRuYwIQ8eef9WIYrGSc2iid","toolName":"read","content":[{"type":"text","text":"---\nname: extract\ndescription: Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.\n---\n\nIdentify reusable patterns, components, and design tokens, then extract and consolidate them into the design system for systematic reuse.\n\n## Discover\n\nAnalyze the target area to identify extraction opportunities:\n\n1. **Find the design system**: Locate your design system, component library, or shared UI directory (grep for \"design system\", \"ui\", \"components\", etc.). Understand its structure:\n - Component organization and naming conventions\n - Design token structure (if any)\n - Documentation patterns\n - Import/export conventions\n \n **CRITICAL**: If no design system exists, ask before creating one. Understand the preferred location and structure first.\n\n2. **Identify patterns**: Look for:\n - **Repeated components**: Similar UI patterns used multiple times (buttons, cards, inputs, etc.)\n - **Hard-coded values**: Colors, spacing, typography, shadows that should be tokens\n - **Inconsistent variations**: Multiple implementations of the same concept (3 different button styles)\n - **Reusable patterns**: Layout patterns, composition patterns, interaction patterns worth systematizing\n\n3. **Assess value**: Not everything should be extracted. Consider:\n - Is this used 3+ times, or likely to be reused?\n - Would systematizing this improve consistency?\n - Is this a general pattern or context-specific?\n - What's the maintenance cost vs benefit?\n\n## Plan Extraction\n\nCreate a systematic extraction plan:\n\n- **Components to extract**: Which UI elements become reusable components?\n- **Tokens to create**: Which hard-coded values become design tokens?\n- **Variants to support**: What variations does each component need?\n- **Naming conventions**: Component names, token names, prop names that match existing patterns\n- **Migration path**: How to refactor existing uses to consume the new shared versions\n\n**IMPORTANT**: Design systems grow incrementally. Extract what's clearly reusable now, not everything that might someday be reusable.\n\n## Extract & Enrich\n\nBuild improved, reusable versions:\n\n- **Components**: Create well-designed components with:\n - Clear props API with sensible defaults\n - Proper variants for different use cases\n - Accessibility built in (ARIA, keyboard navigation, focus management)\n - Documentation and usage examples\n \n- **Design tokens**: Create tokens with:\n - Clear naming (primitive vs semantic)\n - Proper hierarchy and organization\n - Documentation of when to use each token\n \n- **Patterns**: Document patterns with:\n - When to use this pattern\n - Code examples\n - Variations and combinations\n\n**NEVER**:\n- Extract one-off, context-specific implementations without generalization\n- Create components so generic they're useless\n- Extract without considering existing design system conventions\n- Skip proper TypeScript types or prop documentation\n- Create tokens for every single value (tokens should have semantic meaning)\n\n## Migrate\n\nReplace existing uses with the new shared versions:\n\n- **Find all instances**: Search for the patterns you've extracted\n- **Replace systematically**: Update each use to consume the shared version\n- **Test thoroughly**: Ensure visual and functional parity\n- **Delete dead code**: Remove the old implementations\n\n## Document\n\nUpdate design system documentation:\n\n- Add new components to the component library\n- Document token usage and values\n- Add examples and guidelines\n- Update any Storybook or component catalog\n\nRemember: A good design system is a living system. Extract patterns as they emerge, enrich them thoughtfully, and maintain them consistently."}],"isError":false,"timestamp":1775941182726}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":170,"output":18,"cacheRead":2176,"cacheWrite":0,"totalTokens":2364,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"},"toolResults":[{"role":"toolResult","toolCallId":"call_QyRuYwIQ8eef9WIYrGSc2iid","toolName":"read","content":[{"type":"text","text":"---\nname: extract\ndescription: Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.\n---\n\nIdentify reusable patterns, components, and design tokens, then extract and consolidate them into the design system for systematic reuse.\n\n## Discover\n\nAnalyze the target area to identify extraction opportunities:\n\n1. **Find the design system**: Locate your design system, component library, or shared UI directory (grep for \"design system\", \"ui\", \"components\", etc.). Understand its structure:\n - Component organization and naming conventions\n - Design token structure (if any)\n - Documentation patterns\n - Import/export conventions\n \n **CRITICAL**: If no design system exists, ask before creating one. Understand the preferred location and structure first.\n\n2. **Identify patterns**: Look for:\n - **Repeated components**: Similar UI patterns used multiple times (buttons, cards, inputs, etc.)\n - **Hard-coded values**: Colors, spacing, typography, shadows that should be tokens\n - **Inconsistent variations**: Multiple implementations of the same concept (3 different button styles)\n - **Reusable patterns**: Layout patterns, composition patterns, interaction patterns worth systematizing\n\n3. **Assess value**: Not everything should be extracted. Consider:\n - Is this used 3+ times, or likely to be reused?\n - Would systematizing this improve consistency?\n - Is this a general pattern or context-specific?\n - What's the maintenance cost vs benefit?\n\n## Plan Extraction\n\nCreate a systematic extraction plan:\n\n- **Components to extract**: Which UI elements become reusable components?\n- **Tokens to create**: Which hard-coded values become design tokens?\n- **Variants to support**: What variations does each component need?\n- **Naming conventions**: Component names, token names, prop names that match existing patterns\n- **Migration path**: How to refactor existing uses to consume the new shared versions\n\n**IMPORTANT**: Design systems grow incrementally. Extract what's clearly reusable now, not everything that might someday be reusable.\n\n## Extract & Enrich\n\nBuild improved, reusable versions:\n\n- **Components**: Create well-designed components with:\n - Clear props API with sensible defaults\n - Proper variants for different use cases\n - Accessibility built in (ARIA, keyboard navigation, focus management)\n - Documentation and usage examples\n \n- **Design tokens**: Create tokens with:\n - Clear naming (primitive vs semantic)\n - Proper hierarchy and organization\n - Documentation of when to use each token\n \n- **Patterns**: Document patterns with:\n - When to use this pattern\n - Code examples\n - Variations and combinations\n\n**NEVER**:\n- Extract one-off, context-specific implementations without generalization\n- Create components so generic they're useless\n- Extract without considering existing design system conventions\n- Skip proper TypeScript types or prop documentation\n- Create tokens for every single value (tokens should have semantic meaning)\n\n## Migrate\n\nReplace existing uses with the new shared versions:\n\n- **Find all instances**: Search for the patterns you've extracted\n- **Replace systematically**: Update each use to consume the shared version\n- **Test thoroughly**: Ensure visual and functional parity\n- **Delete dead code**: Remove the old implementations\n\n## Document\n\nUpdate design system documentation:\n\n- Add new components to the component library\n- Document token usage and values\n- Add examples and guidelines\n- Update any Storybook or component catalog\n\nRemember: A good design system is a living system. Extract patterns as they emerge, enrich them thoughtfully, and maintain them consistently."}],"isError":false,"timestamp":1775941182726}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"path","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":"{\"path"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{},"partialArgs":"{\"path"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\":\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":""},"partialArgs":"{\"path\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":""},"partialArgs":"{\"path\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"audit","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit"},"partialArgs":"{\"path\":\"audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit"},"partialArgs":"{\"path\":\"audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"/S","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/S"},"partialArgs":"{\"path\":\"audit/S"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/S"},"partialArgs":"{\"path\":\"audit/S"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"K","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SK"},"partialArgs":"{\"path\":\"audit/SK"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SK"},"partialArgs":"{\"path\":\"audit/SK"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"ILL","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL"},"partialArgs":"{\"path\":\"audit/SKILL"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL"},"partialArgs":"{\"path\":\"audit/SKILL"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":".md","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"},"partialArgs":"{\"path\":\"audit/SKILL.md"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"},"partialArgs":"{\"path\":\"audit/SKILL.md"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"},"partialArgs":"{\"path\":\"audit/SKILL.md\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"},"partialArgs":"{\"path\":\"audit/SKILL.md\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":0,"toolCall":{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"}},"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":1154,"output":18,"cacheRead":2048,"cacheWrite":0,"totalTokens":3220,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":1154,"output":18,"cacheRead":2048,"cacheWrite":0,"totalTokens":3220,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":1154,"output":18,"cacheRead":2048,"cacheWrite":0,"totalTokens":3220,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"}}
{"type":"tool_execution_start","toolCallId":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","toolName":"read","args":{"path":"audit/SKILL.md"}}
{"type":"tool_execution_end","toolCallId":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","toolName":"read","result":{"content":[{"type":"text","text":"---\nname: audit\ndescription: Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.\n---\n\n## MANDATORY PREPARATION\n\nInvoke /frontend-design — it contains design principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.\n\n---\n\nRun systematic **technical** quality checks and generate a comprehensive report. Don't fix issues — document them for other commands to address.\n\nThis is a code-level audit, not a design critique. Check what's measurable and verifiable in the implementation.\n\n## Diagnostic Scan\n\nRun comprehensive checks across 5 dimensions. Score each dimension 0-4 using the criteria below.\n\n### 1. Accessibility (A11y)\n\n**Check for**:\n- **Contrast issues**: Text contrast ratios < 4.5:1 (or 7:1 for AAA)\n- **Missing ARIA**: Interactive elements without proper roles, labels, or states\n- **Keyboard navigation**: Missing focus indicators, illogical tab order, keyboard traps\n- **Semantic HTML**: Improper heading hierarchy, missing landmarks, divs instead of buttons\n- **Alt text**: Missing or poor image descriptions\n- **Form issues**: Inputs without labels, poor error messaging, missing required indicators\n\n**Score 0-4**: 0=Inaccessible (fails WCAG A), 1=Major gaps (few ARIA labels, no keyboard nav), 2=Partial (some a11y effort, significant gaps), 3=Good (WCAG AA mostly met, minor gaps), 4=Excellent (WCAG AA fully met, approaches AAA)\n\n### 2. Performance\n\n**Check for**:\n- **Layout thrashing**: Reading/writing layout properties in loops\n- **Expensive animations**: Animating layout properties (width, height, top, left) instead of transform/opacity\n- **Missing optimization**: Images without lazy loading, unoptimized assets, missing will-change\n- **Bundle size**: Unnecessary imports, unused dependencies\n- **Render performance**: Unnecessary re-renders, missing memoization\n\n**Score 0-4**: 0=Severe issues (layout thrash, unoptimized everything), 1=Major problems (no lazy loading, expensive animations), 2=Partial (some optimization, gaps remain), 3=Good (mostly optimized, minor improvements possible), 4=Excellent (fast, lean, well-optimized)\n\n### 3. Theming\n\n**Check for**:\n- **Hard-coded colors**: Colors not using design tokens\n- **Broken dark mode**: Missing dark mode variants, poor contrast in dark theme\n- **Inconsistent tokens**: Using wrong tokens, mixing token types\n- **Theme switching issues**: Values that don't update on theme change\n\n**Score 0-4**: 0=No theming (hard-coded everything), 1=Minimal tokens (mostly hard-coded), 2=Partial (tokens exist but inconsistently used), 3=Good (tokens used, minor hard-coded values), 4=Excellent (full token system, dark mode works perfectly)\n\n### 4. Responsive Design\n\n**Check for**:\n- **Fixed widths**: Hard-coded widths that break on mobile\n- **Touch targets**: Interactive elements < 44x44px\n- **Horizontal scroll**: Content overflow on narrow viewports\n- **Text scaling**: Layouts that break when text size increases\n- **Missing breakpoints**: No mobile/tablet variants\n\n**Score 0-4**: 0=Desktop-only (breaks on mobile), 1=Major issues (some breakpoints, many failures), 2=Partial (works on mobile, rough edges), 3=Good (responsive, minor touch target or overflow issues), 4=Excellent (fluid, all viewports, proper touch targets)\n\n### 5. Anti-Patterns (CRITICAL)\n\nCheck against ALL the **DON'T** guidelines in the frontend-design skill. Look for AI slop tells (AI color palette, gradient text, glassmorphism, hero metrics, card grids, generic fonts) and general design anti-patterns (gray on color, nested cards, bounce easing, redundant copy).\n\n**Score 0-4**: 0=AI slop gallery (5+ tells), 1=Heavy AI aesthetic (3-4 tells), 2=Some tells (1-2 noticeable), 3=Mostly clean (subtle issues only), 4=No AI tells (distinctive, intentional design)\n\n## Generate Report\n\n### Audit Health Score\n\n| # | Dimension | Score | Key Finding |\n|---|-----------|-------|-------------|\n| 1 | Accessibility | ? | [most critical a11y issue or \"--\"] |\n| 2 | Performance | ? | |\n| 3 | Responsive Design | ? | |\n| 4 | Theming | ? | |\n| 5 | Anti-Patterns | ? | |\n| **Total** | | **??/20** | **[Rating band]** |\n\n**Rating bands**: 18-20 Excellent (minor polish), 14-17 Good (address weak dimensions), 10-13 Acceptable (significant work needed), 6-9 Poor (major overhaul), 0-5 Critical (fundamental issues)\n\n### Anti-Patterns Verdict\n**Start here.** Pass/fail: Does this look AI-generated? List specific tells. Be brutally honest.\n\n### Executive Summary\n- Audit Health Score: **??/20** ([rating band])\n- Total issues found (count by severity: P0/P1/P2/P3)\n- Top 3-5 critical issues\n- Recommended next steps\n\n### Detailed Findings by Severity\n\nTag every issue with **P0-P3 severity**:\n- **P0 Blocking**: Prevents task completion — fix immediately\n- **P1 Major**: Significant difficulty or WCAG AA violation — fix before release\n- **P2 Minor**: Annoyance, workaround exists — fix in next pass\n- **P3 Polish**: Nice-to-fix, no real user impact — fix if time permits\n\nFor each issue, document:\n- **[P?] Issue name**\n- **Location**: Component, file, line\n- **Category**: Accessibility / Performance / Theming / Responsive / Anti-Pattern\n- **Impact**: How it affects users\n- **WCAG/Standard**: Which standard it violates (if applicable)\n- **Recommendation**: How to fix it\n- **Suggested command**: Which command to use (prefer: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive)\n\n### Patterns & Systemic Issues\n\nIdentify recurring problems that indicate systemic gaps rather than one-off mistakes:\n- \"Hard-coded colors appear in 15+ components, should use design tokens\"\n- \"Touch targets consistently too small (<44px) throughout mobile experience\"\n\n### Positive Findings\n\nNote what's working well — good practices to maintain and replicate.\n\n## Recommended Actions\n\nList recommended commands in priority order (P0 first, then P1, then P2):\n\n1. **[P?] `/command-name`** — Brief description (specific context from audit findings)\n2. **[P?] `/command-name`** — Brief description (specific context)\n\n**Rules**: Only recommend commands from: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive. Map findings to the most appropriate command. End with `/polish` as the final step if any fixes were recommended.\n\nAfter presenting the summary, tell the user:\n\n> You can ask me to run these one at a time, all at once, or in any order you prefer.\n>\n> Re-run `/audit` after fixes to see your score improve.\n\n**IMPORTANT**: Be thorough but actionable. Too many P3 issues creates noise. Focus on what actually matters.\n\n**NEVER**:\n- Report issues without explaining impact (why does this matter?)\n- Provide generic recommendations (be specific and actionable)\n- Skip positive findings (celebrate what works)\n- Forget to prioritize (everything can't be P0)\n- Report false positives without verification\n\nRemember: You're a technical quality auditor. Document systematically, prioritize ruthlessly, cite specific code locations, and provide clear paths to improvement."}]},"isError":false}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","toolName":"read","content":[{"type":"text","text":"---\nname: audit\ndescription: Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.\n---\n\n## MANDATORY PREPARATION\n\nInvoke /frontend-design — it contains design principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.\n\n---\n\nRun systematic **technical** quality checks and generate a comprehensive report. Don't fix issues — document them for other commands to address.\n\nThis is a code-level audit, not a design critique. Check what's measurable and verifiable in the implementation.\n\n## Diagnostic Scan\n\nRun comprehensive checks across 5 dimensions. Score each dimension 0-4 using the criteria below.\n\n### 1. Accessibility (A11y)\n\n**Check for**:\n- **Contrast issues**: Text contrast ratios < 4.5:1 (or 7:1 for AAA)\n- **Missing ARIA**: Interactive elements without proper roles, labels, or states\n- **Keyboard navigation**: Missing focus indicators, illogical tab order, keyboard traps\n- **Semantic HTML**: Improper heading hierarchy, missing landmarks, divs instead of buttons\n- **Alt text**: Missing or poor image descriptions\n- **Form issues**: Inputs without labels, poor error messaging, missing required indicators\n\n**Score 0-4**: 0=Inaccessible (fails WCAG A), 1=Major gaps (few ARIA labels, no keyboard nav), 2=Partial (some a11y effort, significant gaps), 3=Good (WCAG AA mostly met, minor gaps), 4=Excellent (WCAG AA fully met, approaches AAA)\n\n### 2. Performance\n\n**Check for**:\n- **Layout thrashing**: Reading/writing layout properties in loops\n- **Expensive animations**: Animating layout properties (width, height, top, left) instead of transform/opacity\n- **Missing optimization**: Images without lazy loading, unoptimized assets, missing will-change\n- **Bundle size**: Unnecessary imports, unused dependencies\n- **Render performance**: Unnecessary re-renders, missing memoization\n\n**Score 0-4**: 0=Severe issues (layout thrash, unoptimized everything), 1=Major problems (no lazy loading, expensive animations), 2=Partial (some optimization, gaps remain), 3=Good (mostly optimized, minor improvements possible), 4=Excellent (fast, lean, well-optimized)\n\n### 3. Theming\n\n**Check for**:\n- **Hard-coded colors**: Colors not using design tokens\n- **Broken dark mode**: Missing dark mode variants, poor contrast in dark theme\n- **Inconsistent tokens**: Using wrong tokens, mixing token types\n- **Theme switching issues**: Values that don't update on theme change\n\n**Score 0-4**: 0=No theming (hard-coded everything), 1=Minimal tokens (mostly hard-coded), 2=Partial (tokens exist but inconsistently used), 3=Good (tokens used, minor hard-coded values), 4=Excellent (full token system, dark mode works perfectly)\n\n### 4. Responsive Design\n\n**Check for**:\n- **Fixed widths**: Hard-coded widths that break on mobile\n- **Touch targets**: Interactive elements < 44x44px\n- **Horizontal scroll**: Content overflow on narrow viewports\n- **Text scaling**: Layouts that break when text size increases\n- **Missing breakpoints**: No mobile/tablet variants\n\n**Score 0-4**: 0=Desktop-only (breaks on mobile), 1=Major issues (some breakpoints, many failures), 2=Partial (works on mobile, rough edges), 3=Good (responsive, minor touch target or overflow issues), 4=Excellent (fluid, all viewports, proper touch targets)\n\n### 5. Anti-Patterns (CRITICAL)\n\nCheck against ALL the **DON'T** guidelines in the frontend-design skill. Look for AI slop tells (AI color palette, gradient text, glassmorphism, hero metrics, card grids, generic fonts) and general design anti-patterns (gray on color, nested cards, bounce easing, redundant copy).\n\n**Score 0-4**: 0=AI slop gallery (5+ tells), 1=Heavy AI aesthetic (3-4 tells), 2=Some tells (1-2 noticeable), 3=Mostly clean (subtle issues only), 4=No AI tells (distinctive, intentional design)\n\n## Generate Report\n\n### Audit Health Score\n\n| # | Dimension | Score | Key Finding |\n|---|-----------|-------|-------------|\n| 1 | Accessibility | ? | [most critical a11y issue or \"--\"] |\n| 2 | Performance | ? | |\n| 3 | Responsive Design | ? | |\n| 4 | Theming | ? | |\n| 5 | Anti-Patterns | ? | |\n| **Total** | | **??/20** | **[Rating band]** |\n\n**Rating bands**: 18-20 Excellent (minor polish), 14-17 Good (address weak dimensions), 10-13 Acceptable (significant work needed), 6-9 Poor (major overhaul), 0-5 Critical (fundamental issues)\n\n### Anti-Patterns Verdict\n**Start here.** Pass/fail: Does this look AI-generated? List specific tells. Be brutally honest.\n\n### Executive Summary\n- Audit Health Score: **??/20** ([rating band])\n- Total issues found (count by severity: P0/P1/P2/P3)\n- Top 3-5 critical issues\n- Recommended next steps\n\n### Detailed Findings by Severity\n\nTag every issue with **P0-P3 severity**:\n- **P0 Blocking**: Prevents task completion — fix immediately\n- **P1 Major**: Significant difficulty or WCAG AA violation — fix before release\n- **P2 Minor**: Annoyance, workaround exists — fix in next pass\n- **P3 Polish**: Nice-to-fix, no real user impact — fix if time permits\n\nFor each issue, document:\n- **[P?] Issue name**\n- **Location**: Component, file, line\n- **Category**: Accessibility / Performance / Theming / Responsive / Anti-Pattern\n- **Impact**: How it affects users\n- **WCAG/Standard**: Which standard it violates (if applicable)\n- **Recommendation**: How to fix it\n- **Suggested command**: Which command to use (prefer: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive)\n\n### Patterns & Systemic Issues\n\nIdentify recurring problems that indicate systemic gaps rather than one-off mistakes:\n- \"Hard-coded colors appear in 15+ components, should use design tokens\"\n- \"Touch targets consistently too small (<44px) throughout mobile experience\"\n\n### Positive Findings\n\nNote what's working well — good practices to maintain and replicate.\n\n## Recommended Actions\n\nList recommended commands in priority order (P0 first, then P1, then P2):\n\n1. **[P?] `/command-name`** — Brief description (specific context from audit findings)\n2. **[P?] `/command-name`** — Brief description (specific context)\n\n**Rules**: Only recommend commands from: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive. Map findings to the most appropriate command. End with `/polish` as the final step if any fixes were recommended.\n\nAfter presenting the summary, tell the user:\n\n> You can ask me to run these one at a time, all at once, or in any order you prefer.\n>\n> Re-run `/audit` after fixes to see your score improve.\n\n**IMPORTANT**: Be thorough but actionable. Too many P3 issues creates noise. Focus on what actually matters.\n\n**NEVER**:\n- Report issues without explaining impact (why does this matter?)\n- Provide generic recommendations (be specific and actionable)\n- Skip positive findings (celebrate what works)\n- Forget to prioritize (everything can't be P0)\n- Report false positives without verification\n\nRemember: You're a technical quality auditor. Document systematically, prioritize ruthlessly, cite specific code locations, and provide clear paths to improvement."}],"isError":false,"timestamp":1775941183908}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","toolName":"read","content":[{"type":"text","text":"---\nname: audit\ndescription: Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.\n---\n\n## MANDATORY PREPARATION\n\nInvoke /frontend-design — it contains design principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.\n\n---\n\nRun systematic **technical** quality checks and generate a comprehensive report. Don't fix issues — document them for other commands to address.\n\nThis is a code-level audit, not a design critique. Check what's measurable and verifiable in the implementation.\n\n## Diagnostic Scan\n\nRun comprehensive checks across 5 dimensions. Score each dimension 0-4 using the criteria below.\n\n### 1. Accessibility (A11y)\n\n**Check for**:\n- **Contrast issues**: Text contrast ratios < 4.5:1 (or 7:1 for AAA)\n- **Missing ARIA**: Interactive elements without proper roles, labels, or states\n- **Keyboard navigation**: Missing focus indicators, illogical tab order, keyboard traps\n- **Semantic HTML**: Improper heading hierarchy, missing landmarks, divs instead of buttons\n- **Alt text**: Missing or poor image descriptions\n- **Form issues**: Inputs without labels, poor error messaging, missing required indicators\n\n**Score 0-4**: 0=Inaccessible (fails WCAG A), 1=Major gaps (few ARIA labels, no keyboard nav), 2=Partial (some a11y effort, significant gaps), 3=Good (WCAG AA mostly met, minor gaps), 4=Excellent (WCAG AA fully met, approaches AAA)\n\n### 2. Performance\n\n**Check for**:\n- **Layout thrashing**: Reading/writing layout properties in loops\n- **Expensive animations**: Animating layout properties (width, height, top, left) instead of transform/opacity\n- **Missing optimization**: Images without lazy loading, unoptimized assets, missing will-change\n- **Bundle size**: Unnecessary imports, unused dependencies\n- **Render performance**: Unnecessary re-renders, missing memoization\n\n**Score 0-4**: 0=Severe issues (layout thrash, unoptimized everything), 1=Major problems (no lazy loading, expensive animations), 2=Partial (some optimization, gaps remain), 3=Good (mostly optimized, minor improvements possible), 4=Excellent (fast, lean, well-optimized)\n\n### 3. Theming\n\n**Check for**:\n- **Hard-coded colors**: Colors not using design tokens\n- **Broken dark mode**: Missing dark mode variants, poor contrast in dark theme\n- **Inconsistent tokens**: Using wrong tokens, mixing token types\n- **Theme switching issues**: Values that don't update on theme change\n\n**Score 0-4**: 0=No theming (hard-coded everything), 1=Minimal tokens (mostly hard-coded), 2=Partial (tokens exist but inconsistently used), 3=Good (tokens used, minor hard-coded values), 4=Excellent (full token system, dark mode works perfectly)\n\n### 4. Responsive Design\n\n**Check for**:\n- **Fixed widths**: Hard-coded widths that break on mobile\n- **Touch targets**: Interactive elements < 44x44px\n- **Horizontal scroll**: Content overflow on narrow viewports\n- **Text scaling**: Layouts that break when text size increases\n- **Missing breakpoints**: No mobile/tablet variants\n\n**Score 0-4**: 0=Desktop-only (breaks on mobile), 1=Major issues (some breakpoints, many failures), 2=Partial (works on mobile, rough edges), 3=Good (responsive, minor touch target or overflow issues), 4=Excellent (fluid, all viewports, proper touch targets)\n\n### 5. Anti-Patterns (CRITICAL)\n\nCheck against ALL the **DON'T** guidelines in the frontend-design skill. Look for AI slop tells (AI color palette, gradient text, glassmorphism, hero metrics, card grids, generic fonts) and general design anti-patterns (gray on color, nested cards, bounce easing, redundant copy).\n\n**Score 0-4**: 0=AI slop gallery (5+ tells), 1=Heavy AI aesthetic (3-4 tells), 2=Some tells (1-2 noticeable), 3=Mostly clean (subtle issues only), 4=No AI tells (distinctive, intentional design)\n\n## Generate Report\n\n### Audit Health Score\n\n| # | Dimension | Score | Key Finding |\n|---|-----------|-------|-------------|\n| 1 | Accessibility | ? | [most critical a11y issue or \"--\"] |\n| 2 | Performance | ? | |\n| 3 | Responsive Design | ? | |\n| 4 | Theming | ? | |\n| 5 | Anti-Patterns | ? | |\n| **Total** | | **??/20** | **[Rating band]** |\n\n**Rating bands**: 18-20 Excellent (minor polish), 14-17 Good (address weak dimensions), 10-13 Acceptable (significant work needed), 6-9 Poor (major overhaul), 0-5 Critical (fundamental issues)\n\n### Anti-Patterns Verdict\n**Start here.** Pass/fail: Does this look AI-generated? List specific tells. Be brutally honest.\n\n### Executive Summary\n- Audit Health Score: **??/20** ([rating band])\n- Total issues found (count by severity: P0/P1/P2/P3)\n- Top 3-5 critical issues\n- Recommended next steps\n\n### Detailed Findings by Severity\n\nTag every issue with **P0-P3 severity**:\n- **P0 Blocking**: Prevents task completion — fix immediately\n- **P1 Major**: Significant difficulty or WCAG AA violation — fix before release\n- **P2 Minor**: Annoyance, workaround exists — fix in next pass\n- **P3 Polish**: Nice-to-fix, no real user impact — fix if time permits\n\nFor each issue, document:\n- **[P?] Issue name**\n- **Location**: Component, file, line\n- **Category**: Accessibility / Performance / Theming / Responsive / Anti-Pattern\n- **Impact**: How it affects users\n- **WCAG/Standard**: Which standard it violates (if applicable)\n- **Recommendation**: How to fix it\n- **Suggested command**: Which command to use (prefer: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive)\n\n### Patterns & Systemic Issues\n\nIdentify recurring problems that indicate systemic gaps rather than one-off mistakes:\n- \"Hard-coded colors appear in 15+ components, should use design tokens\"\n- \"Touch targets consistently too small (<44px) throughout mobile experience\"\n\n### Positive Findings\n\nNote what's working well — good practices to maintain and replicate.\n\n## Recommended Actions\n\nList recommended commands in priority order (P0 first, then P1, then P2):\n\n1. **[P?] `/command-name`** — Brief description (specific context from audit findings)\n2. **[P?] `/command-name`** — Brief description (specific context)\n\n**Rules**: Only recommend commands from: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive. Map findings to the most appropriate command. End with `/polish` as the final step if any fixes were recommended.\n\nAfter presenting the summary, tell the user:\n\n> You can ask me to run these one at a time, all at once, or in any order you prefer.\n>\n> Re-run `/audit` after fixes to see your score improve.\n\n**IMPORTANT**: Be thorough but actionable. Too many P3 issues creates noise. Focus on what actually matters.\n\n**NEVER**:\n- Report issues without explaining impact (why does this matter?)\n- Provide generic recommendations (be specific and actionable)\n- Skip positive findings (celebrate what works)\n- Forget to prioritize (everything can't be P0)\n- Report false positives without verification\n\nRemember: You're a technical quality auditor. Document systematically, prioritize ruthlessly, cite specific code locations, and provide clear paths to improvement."}],"isError":false,"timestamp":1775941183908}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":1154,"output":18,"cacheRead":2048,"cacheWrite":0,"totalTokens":3220,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"},"toolResults":[{"role":"toolResult","toolCallId":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","toolName":"read","content":[{"type":"text","text":"---\nname: audit\ndescription: Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.\n---\n\n## MANDATORY PREPARATION\n\nInvoke /frontend-design — it contains design principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.\n\n---\n\nRun systematic **technical** quality checks and generate a comprehensive report. Don't fix issues — document them for other commands to address.\n\nThis is a code-level audit, not a design critique. Check what's measurable and verifiable in the implementation.\n\n## Diagnostic Scan\n\nRun comprehensive checks across 5 dimensions. Score each dimension 0-4 using the criteria below.\n\n### 1. Accessibility (A11y)\n\n**Check for**:\n- **Contrast issues**: Text contrast ratios < 4.5:1 (or 7:1 for AAA)\n- **Missing ARIA**: Interactive elements without proper roles, labels, or states\n- **Keyboard navigation**: Missing focus indicators, illogical tab order, keyboard traps\n- **Semantic HTML**: Improper heading hierarchy, missing landmarks, divs instead of buttons\n- **Alt text**: Missing or poor image descriptions\n- **Form issues**: Inputs without labels, poor error messaging, missing required indicators\n\n**Score 0-4**: 0=Inaccessible (fails WCAG A), 1=Major gaps (few ARIA labels, no keyboard nav), 2=Partial (some a11y effort, significant gaps), 3=Good (WCAG AA mostly met, minor gaps), 4=Excellent (WCAG AA fully met, approaches AAA)\n\n### 2. Performance\n\n**Check for**:\n- **Layout thrashing**: Reading/writing layout properties in loops\n- **Expensive animations**: Animating layout properties (width, height, top, left) instead of transform/opacity\n- **Missing optimization**: Images without lazy loading, unoptimized assets, missing will-change\n- **Bundle size**: Unnecessary imports, unused dependencies\n- **Render performance**: Unnecessary re-renders, missing memoization\n\n**Score 0-4**: 0=Severe issues (layout thrash, unoptimized everything), 1=Major problems (no lazy loading, expensive animations), 2=Partial (some optimization, gaps remain), 3=Good (mostly optimized, minor improvements possible), 4=Excellent (fast, lean, well-optimized)\n\n### 3. Theming\n\n**Check for**:\n- **Hard-coded colors**: Colors not using design tokens\n- **Broken dark mode**: Missing dark mode variants, poor contrast in dark theme\n- **Inconsistent tokens**: Using wrong tokens, mixing token types\n- **Theme switching issues**: Values that don't update on theme change\n\n**Score 0-4**: 0=No theming (hard-coded everything), 1=Minimal tokens (mostly hard-coded), 2=Partial (tokens exist but inconsistently used), 3=Good (tokens used, minor hard-coded values), 4=Excellent (full token system, dark mode works perfectly)\n\n### 4. Responsive Design\n\n**Check for**:\n- **Fixed widths**: Hard-coded widths that break on mobile\n- **Touch targets**: Interactive elements < 44x44px\n- **Horizontal scroll**: Content overflow on narrow viewports\n- **Text scaling**: Layouts that break when text size increases\n- **Missing breakpoints**: No mobile/tablet variants\n\n**Score 0-4**: 0=Desktop-only (breaks on mobile), 1=Major issues (some breakpoints, many failures), 2=Partial (works on mobile, rough edges), 3=Good (responsive, minor touch target or overflow issues), 4=Excellent (fluid, all viewports, proper touch targets)\n\n### 5. Anti-Patterns (CRITICAL)\n\nCheck against ALL the **DON'T** guidelines in the frontend-design skill. Look for AI slop tells (AI color palette, gradient text, glassmorphism, hero metrics, card grids, generic fonts) and general design anti-patterns (gray on color, nested cards, bounce easing, redundant copy).\n\n**Score 0-4**: 0=AI slop gallery (5+ tells), 1=Heavy AI aesthetic (3-4 tells), 2=Some tells (1-2 noticeable), 3=Mostly clean (subtle issues only), 4=No AI tells (distinctive, intentional design)\n\n## Generate Report\n\n### Audit Health Score\n\n| # | Dimension | Score | Key Finding |\n|---|-----------|-------|-------------|\n| 1 | Accessibility | ? | [most critical a11y issue or \"--\"] |\n| 2 | Performance | ? | |\n| 3 | Responsive Design | ? | |\n| 4 | Theming | ? | |\n| 5 | Anti-Patterns | ? | |\n| **Total** | | **??/20** | **[Rating band]** |\n\n**Rating bands**: 18-20 Excellent (minor polish), 14-17 Good (address weak dimensions), 10-13 Acceptable (significant work needed), 6-9 Poor (major overhaul), 0-5 Critical (fundamental issues)\n\n### Anti-Patterns Verdict\n**Start here.** Pass/fail: Does this look AI-generated? List specific tells. Be brutally honest.\n\n### Executive Summary\n- Audit Health Score: **??/20** ([rating band])\n- Total issues found (count by severity: P0/P1/P2/P3)\n- Top 3-5 critical issues\n- Recommended next steps\n\n### Detailed Findings by Severity\n\nTag every issue with **P0-P3 severity**:\n- **P0 Blocking**: Prevents task completion — fix immediately\n- **P1 Major**: Significant difficulty or WCAG AA violation — fix before release\n- **P2 Minor**: Annoyance, workaround exists — fix in next pass\n- **P3 Polish**: Nice-to-fix, no real user impact — fix if time permits\n\nFor each issue, document:\n- **[P?] Issue name**\n- **Location**: Component, file, line\n- **Category**: Accessibility / Performance / Theming / Responsive / Anti-Pattern\n- **Impact**: How it affects users\n- **WCAG/Standard**: Which standard it violates (if applicable)\n- **Recommendation**: How to fix it\n- **Suggested command**: Which command to use (prefer: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive)\n\n### Patterns & Systemic Issues\n\nIdentify recurring problems that indicate systemic gaps rather than one-off mistakes:\n- \"Hard-coded colors appear in 15+ components, should use design tokens\"\n- \"Touch targets consistently too small (<44px) throughout mobile experience\"\n\n### Positive Findings\n\nNote what's working well — good practices to maintain and replicate.\n\n## Recommended Actions\n\nList recommended commands in priority order (P0 first, then P1, then P2):\n\n1. **[P?] `/command-name`** — Brief description (specific context from audit findings)\n2. **[P?] `/command-name`** — Brief description (specific context)\n\n**Rules**: Only recommend commands from: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive. Map findings to the most appropriate command. End with `/polish` as the final step if any fixes were recommended.\n\nAfter presenting the summary, tell the user:\n\n> You can ask me to run these one at a time, all at once, or in any order you prefer.\n>\n> Re-run `/audit` after fixes to see your score improve.\n\n**IMPORTANT**: Be thorough but actionable. Too many P3 issues creates noise. Focus on what actually matters.\n\n**NEVER**:\n- Report issues without explaining impact (why does this matter?)\n- Provide generic recommendations (be specific and actionable)\n- Skip positive findings (celebrate what works)\n- Forget to prioritize (everything can't be P0)\n- Report false positives without verification\n\nRemember: You're a technical quality auditor. Document systematically, prioritize ruthlessly, cite specific code locations, and provide clear paths to improvement."}],"isError":false,"timestamp":1775941183908}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"{\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":"{\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"path","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":"{\"path"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{},"partialArgs":"{\"path"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\":\"","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":""},"partialArgs":"{\"path\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":""},"partialArgs":"{\"path\":\""}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend"},"partialArgs":"{\"path\":\"frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend"},"partialArgs":"{\"path\":\"frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design"},"partialArgs":"{\"path\":\"frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design"},"partialArgs":"{\"path\":\"frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"/S","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/S"},"partialArgs":"{\"path\":\"frontend-design/S"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/S"},"partialArgs":"{\"path\":\"frontend-design/S"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"K","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SK"},"partialArgs":"{\"path\":\"frontend-design/SK"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SK"},"partialArgs":"{\"path\":\"frontend-design/SK"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"ILL","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL"},"partialArgs":"{\"path\":\"frontend-design/SKILL"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL"},"partialArgs":"{\"path\":\"frontend-design/SKILL"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":".md","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"},"partialArgs":"{\"path\":\"frontend-design/SKILL.md"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"},"partialArgs":"{\"path\":\"frontend-design/SKILL.md"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_delta","contentIndex":0,"delta":"\"}","partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"},"partialArgs":"{\"path\":\"frontend-design/SKILL.md\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"},"partialArgs":"{\"path\":\"frontend-design/SKILL.md\"}"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_update","assistantMessageEvent":{"type":"toolcall_end","contentIndex":0,"toolCall":{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"}},"partial":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":5554,"output":19,"cacheRead":0,"cacheWrite":0,"totalTokens":5573,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}},"message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":5554,"output":19,"cacheRead":0,"cacheWrite":0,"totalTokens":5573,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":5554,"output":19,"cacheRead":0,"cacheWrite":0,"totalTokens":5573,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"}}
{"type":"tool_execution_start","toolCallId":"call_UzN6ivG1lG5v82d7bFgDFU4M","toolName":"read","args":{"path":"frontend-design/SKILL.md"}}
{"type":"tool_execution_end","toolCallId":"call_UzN6ivG1lG5v82d7bFgDFU4M","toolName":"read","result":{"content":[{"type":"text","text":"---\nname: frontend-design\ndescription: Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.\nlicense: Apache 2.0. Based on Anthropic's frontend-design skill. See NOTICE.md for attribution.\n---\n\nThis skill guides creation of distinctive, production-grade frontend interfaces that avoid generic \"AI slop\" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.\n\n## Context Gathering Protocol\n\nDesign skills produce generic output without project context. You MUST have confirmed design context before doing any design work.\n\n**Required context** — every design skill needs at minimum:\n- **Target audience**: Who uses this product and in what context?\n- **Use cases**: What jobs are they trying to get done?\n- **Brand personality/tone**: How should the interface feel?\n\nIndividual skills may require additional context — check the skill's preparation section for specifics.\n\n**CRITICAL**: You cannot infer this context by reading the codebase. Code tells you what was built, not who it's for or what it should feel like. Only the creator can provide this context.\n\n**Gathering order:**\n1. **Check current instructions (instant)**: If your loaded instructions already contain a **Design Context** section, proceed immediately.\n2. **Check .impeccable.md (fast)**: If not in instructions, read `.impeccable.md` from the project root. If it exists and contains the required context, proceed.\n3. **Run teach-impeccable (REQUIRED)**: If neither source has context, you MUST run /teach-impeccable NOW before doing anything else. Do NOT skip this step. Do NOT attempt to infer context from the codebase instead.\n\n---\n\n## Design Direction\n\nCommit to a BOLD aesthetic direction:\n- **Purpose**: What problem does this interface solve? Who uses it?\n- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.\n- **Constraints**: Technical requirements (framework, performance, accessibility).\n- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?\n\n**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work—the key is intentionality, not intensity.\n\nThen implement working code that is:\n- Production-grade and functional\n- Visually striking and memorable\n- Cohesive with a clear aesthetic point-of-view\n- Meticulously refined in every detail\n\n## Frontend Aesthetics Guidelines\n\n### Typography\n→ *Consult [typography reference](reference/typography.md) for scales, pairing, and loading strategies.*\n\nChoose fonts that are beautiful, unique, and interesting. Pair a distinctive display font with a refined body font.\n\n**DO**: Use a modular type scale with fluid sizing (clamp)\n**DO**: Vary font weights and sizes to create clear visual hierarchy\n**DON'T**: Use overused fonts—Inter, Roboto, Arial, Open Sans, system defaults\n**DON'T**: Use monospace typography as lazy shorthand for \"technical/developer\" vibes\n**DON'T**: Put large icons with rounded corners above every heading—they rarely add value and make sites look templated\n\n### Color & Theme\n→ *Consult [color reference](reference/color-and-contrast.md) for OKLCH, palettes, and dark mode.*\n\nCommit to a cohesive palette. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.\n\n**DO**: Use modern CSS color functions (oklch, color-mix, light-dark) for perceptually uniform, maintainable palettes\n**DO**: Tint your neutrals toward your brand hue—even a subtle hint creates subconscious cohesion\n**DON'T**: Use gray text on colored backgrounds—it looks washed out; use a shade of the background color instead\n**DON'T**: Use pure black (#000) or pure white (#fff)—always tint; pure black/white never appears in nature\n**DON'T**: Use the AI color palette: cyan-on-dark, purple-to-blue gradients, neon accents on dark backgrounds\n**DON'T**: Use gradient text for \"impact\"—especially on metrics or headings; it's decorative rather than meaningful\n**DON'T**: Default to dark mode with glowing accents—it looks \"cool\" without requiring actual design decisions\n\n### Layout & Space\n→ *Consult [spatial reference](reference/spatial-design.md) for grids, rhythm, and container queries.*\n\nCreate visual rhythm through varied spacing—not the same padding everywhere. Embrace asymmetry and unexpected compositions. Break the grid intentionally for emphasis.\n\n**DO**: Create visual rhythm through varied spacing—tight groupings, generous separations\n**DO**: Use fluid spacing with clamp() that breathes on larger screens\n**DO**: Use asymmetry and unexpected compositions; break the grid intentionally for emphasis\n**DON'T**: Wrap everything in cards—not everything needs a container\n**DON'T**: Nest cards inside cards—visual noise, flatten the hierarchy\n**DON'T**: Use identical card grids—same-sized cards with icon + heading + text, repeated endlessly\n**DON'T**: Use the hero metric layout template—big number, small label, supporting stats, gradient accent\n**DON'T**: Center everything—left-aligned text with asymmetric layouts feels more designed\n**DON'T**: Use the same spacing everywhere—without rhythm, layouts feel monotonous\n\n### Visual Details\n**DO**: Use intentional, purposeful decorative elements that reinforce brand\n**DON'T**: Use glassmorphism everywhere—blur effects, glass cards, glow borders used decoratively rather than purposefully\n**DON'T**: Use rounded elements with thick colored border on one side—a lazy accent that almost never looks intentional\n**DON'T**: Use sparklines as decoration—tiny charts that look sophisticated but convey nothing meaningful\n**DON'T**: Use rounded rectangles with generic drop shadows—safe, forgettable, could be any AI output\n**DON'T**: Use modals unless there's truly no better alternative—modals are lazy\n\n### Motion\n→ *Consult [motion reference](reference/motion-design.md) for timing, easing, and reduced motion.*\n\nFocus on high-impact moments: one well-orchestrated page load with staggered reveals creates more delight than scattered micro-interactions.\n\n**DO**: Use motion to convey state changes—entrances, exits, feedback\n**DO**: Use exponential easing (ease-out-quart/quint/expo) for natural deceleration\n**DO**: For height animations, use grid-template-rows transitions instead of animating height directly\n**DON'T**: Animate layout properties (width, height, padding, margin)—use transform and opacity only\n**DON'T**: Use bounce or elastic easing—they feel dated and tacky; real objects decelerate smoothly\n\n### Interaction\n→ *Consult [interaction reference](reference/interaction-design.md) for forms, focus, and loading patterns.*\n\nMake interactions feel fast. Use optimistic UI—update immediately, sync later.\n\n**DO**: Use progressive disclosure—start simple, reveal sophistication through interaction (basic options first, advanced behind expandable sections; hover states that reveal secondary actions)\n**DO**: Design empty states that teach the interface, not just say \"nothing here\"\n**DO**: Make every interactive surface feel intentional and responsive\n**DON'T**: Repeat the same information—redundant headers, intros that restate the heading\n**DON'T**: Make every button primary—use ghost buttons, text links, secondary styles; hierarchy matters\n\n### Responsive\n→ *Consult [responsive reference](reference/responsive-design.md) for mobile-first, fluid design, and container queries.*\n\n**DO**: Use container queries (@container) for component-level responsiveness\n**DO**: Adapt the interface for different contexts—don't just shrink it\n**DON'T**: Hide critical functionality on mobile—adapt the interface, don't amputate it\n\n### UX Writing\n→ *Consult [ux-writing reference](reference/ux-writing.md) for labels, errors, and empty states.*\n\n**DO**: Make every word earn its place\n**DON'T**: Repeat information users can already see\n\n---\n\n## The AI Slop Test\n\n**Critical quality check**: If you showed this interface to someone and said \"AI made this,\" would they believe you immediately? If yes, that's the problem.\n\nA distinctive interface should make someone ask \"how was this made?\" not \"which AI made this?\"\n\nReview the DON'T guidelines above—they are the fingerprints of AI-generated work from 2024-2025.\n\n---\n\n## Implementation Principles\n\nMatch implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details.\n\nInterpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices across generations.\n\nRemember: the model is capable of extraordinary creative work. Don't hold back—show what can truly be created when thinking outside the box and committing fully to a distinctive vision."}]},"isError":false}
{"type":"message_start","message":{"role":"toolResult","toolCallId":"call_UzN6ivG1lG5v82d7bFgDFU4M","toolName":"read","content":[{"type":"text","text":"---\nname: frontend-design\ndescription: Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.\nlicense: Apache 2.0. Based on Anthropic's frontend-design skill. See NOTICE.md for attribution.\n---\n\nThis skill guides creation of distinctive, production-grade frontend interfaces that avoid generic \"AI slop\" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.\n\n## Context Gathering Protocol\n\nDesign skills produce generic output without project context. You MUST have confirmed design context before doing any design work.\n\n**Required context** — every design skill needs at minimum:\n- **Target audience**: Who uses this product and in what context?\n- **Use cases**: What jobs are they trying to get done?\n- **Brand personality/tone**: How should the interface feel?\n\nIndividual skills may require additional context — check the skill's preparation section for specifics.\n\n**CRITICAL**: You cannot infer this context by reading the codebase. Code tells you what was built, not who it's for or what it should feel like. Only the creator can provide this context.\n\n**Gathering order:**\n1. **Check current instructions (instant)**: If your loaded instructions already contain a **Design Context** section, proceed immediately.\n2. **Check .impeccable.md (fast)**: If not in instructions, read `.impeccable.md` from the project root. If it exists and contains the required context, proceed.\n3. **Run teach-impeccable (REQUIRED)**: If neither source has context, you MUST run /teach-impeccable NOW before doing anything else. Do NOT skip this step. Do NOT attempt to infer context from the codebase instead.\n\n---\n\n## Design Direction\n\nCommit to a BOLD aesthetic direction:\n- **Purpose**: What problem does this interface solve? Who uses it?\n- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.\n- **Constraints**: Technical requirements (framework, performance, accessibility).\n- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?\n\n**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work—the key is intentionality, not intensity.\n\nThen implement working code that is:\n- Production-grade and functional\n- Visually striking and memorable\n- Cohesive with a clear aesthetic point-of-view\n- Meticulously refined in every detail\n\n## Frontend Aesthetics Guidelines\n\n### Typography\n→ *Consult [typography reference](reference/typography.md) for scales, pairing, and loading strategies.*\n\nChoose fonts that are beautiful, unique, and interesting. Pair a distinctive display font with a refined body font.\n\n**DO**: Use a modular type scale with fluid sizing (clamp)\n**DO**: Vary font weights and sizes to create clear visual hierarchy\n**DON'T**: Use overused fonts—Inter, Roboto, Arial, Open Sans, system defaults\n**DON'T**: Use monospace typography as lazy shorthand for \"technical/developer\" vibes\n**DON'T**: Put large icons with rounded corners above every heading—they rarely add value and make sites look templated\n\n### Color & Theme\n→ *Consult [color reference](reference/color-and-contrast.md) for OKLCH, palettes, and dark mode.*\n\nCommit to a cohesive palette. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.\n\n**DO**: Use modern CSS color functions (oklch, color-mix, light-dark) for perceptually uniform, maintainable palettes\n**DO**: Tint your neutrals toward your brand hue—even a subtle hint creates subconscious cohesion\n**DON'T**: Use gray text on colored backgrounds—it looks washed out; use a shade of the background color instead\n**DON'T**: Use pure black (#000) or pure white (#fff)—always tint; pure black/white never appears in nature\n**DON'T**: Use the AI color palette: cyan-on-dark, purple-to-blue gradients, neon accents on dark backgrounds\n**DON'T**: Use gradient text for \"impact\"—especially on metrics or headings; it's decorative rather than meaningful\n**DON'T**: Default to dark mode with glowing accents—it looks \"cool\" without requiring actual design decisions\n\n### Layout & Space\n→ *Consult [spatial reference](reference/spatial-design.md) for grids, rhythm, and container queries.*\n\nCreate visual rhythm through varied spacing—not the same padding everywhere. Embrace asymmetry and unexpected compositions. Break the grid intentionally for emphasis.\n\n**DO**: Create visual rhythm through varied spacing—tight groupings, generous separations\n**DO**: Use fluid spacing with clamp() that breathes on larger screens\n**DO**: Use asymmetry and unexpected compositions; break the grid intentionally for emphasis\n**DON'T**: Wrap everything in cards—not everything needs a container\n**DON'T**: Nest cards inside cards—visual noise, flatten the hierarchy\n**DON'T**: Use identical card grids—same-sized cards with icon + heading + text, repeated endlessly\n**DON'T**: Use the hero metric layout template—big number, small label, supporting stats, gradient accent\n**DON'T**: Center everything—left-aligned text with asymmetric layouts feels more designed\n**DON'T**: Use the same spacing everywhere—without rhythm, layouts feel monotonous\n\n### Visual Details\n**DO**: Use intentional, purposeful decorative elements that reinforce brand\n**DON'T**: Use glassmorphism everywhere—blur effects, glass cards, glow borders used decoratively rather than purposefully\n**DON'T**: Use rounded elements with thick colored border on one side—a lazy accent that almost never looks intentional\n**DON'T**: Use sparklines as decoration—tiny charts that look sophisticated but convey nothing meaningful\n**DON'T**: Use rounded rectangles with generic drop shadows—safe, forgettable, could be any AI output\n**DON'T**: Use modals unless there's truly no better alternative—modals are lazy\n\n### Motion\n→ *Consult [motion reference](reference/motion-design.md) for timing, easing, and reduced motion.*\n\nFocus on high-impact moments: one well-orchestrated page load with staggered reveals creates more delight than scattered micro-interactions.\n\n**DO**: Use motion to convey state changes—entrances, exits, feedback\n**DO**: Use exponential easing (ease-out-quart/quint/expo) for natural deceleration\n**DO**: For height animations, use grid-template-rows transitions instead of animating height directly\n**DON'T**: Animate layout properties (width, height, padding, margin)—use transform and opacity only\n**DON'T**: Use bounce or elastic easing—they feel dated and tacky; real objects decelerate smoothly\n\n### Interaction\n→ *Consult [interaction reference](reference/interaction-design.md) for forms, focus, and loading patterns.*\n\nMake interactions feel fast. Use optimistic UI—update immediately, sync later.\n\n**DO**: Use progressive disclosure—start simple, reveal sophistication through interaction (basic options first, advanced behind expandable sections; hover states that reveal secondary actions)\n**DO**: Design empty states that teach the interface, not just say \"nothing here\"\n**DO**: Make every interactive surface feel intentional and responsive\n**DON'T**: Repeat the same information—redundant headers, intros that restate the heading\n**DON'T**: Make every button primary—use ghost buttons, text links, secondary styles; hierarchy matters\n\n### Responsive\n→ *Consult [responsive reference](reference/responsive-design.md) for mobile-first, fluid design, and container queries.*\n\n**DO**: Use container queries (@container) for component-level responsiveness\n**DO**: Adapt the interface for different contexts—don't just shrink it\n**DON'T**: Hide critical functionality on mobile—adapt the interface, don't amputate it\n\n### UX Writing\n→ *Consult [ux-writing reference](reference/ux-writing.md) for labels, errors, and empty states.*\n\n**DO**: Make every word earn its place\n**DON'T**: Repeat information users can already see\n\n---\n\n## The AI Slop Test\n\n**Critical quality check**: If you showed this interface to someone and said \"AI made this,\" would they believe you immediately? If yes, that's the problem.\n\nA distinctive interface should make someone ask \"how was this made?\" not \"which AI made this?\"\n\nReview the DON'T guidelines above—they are the fingerprints of AI-generated work from 2024-2025.\n\n---\n\n## Implementation Principles\n\nMatch implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details.\n\nInterpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices across generations.\n\nRemember: the model is capable of extraordinary creative work. Don't hold back—show what can truly be created when thinking outside the box and committing fully to a distinctive vision."}],"isError":false,"timestamp":1775941185214}}
{"type":"message_end","message":{"role":"toolResult","toolCallId":"call_UzN6ivG1lG5v82d7bFgDFU4M","toolName":"read","content":[{"type":"text","text":"---\nname: frontend-design\ndescription: Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.\nlicense: Apache 2.0. Based on Anthropic's frontend-design skill. See NOTICE.md for attribution.\n---\n\nThis skill guides creation of distinctive, production-grade frontend interfaces that avoid generic \"AI slop\" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.\n\n## Context Gathering Protocol\n\nDesign skills produce generic output without project context. You MUST have confirmed design context before doing any design work.\n\n**Required context** — every design skill needs at minimum:\n- **Target audience**: Who uses this product and in what context?\n- **Use cases**: What jobs are they trying to get done?\n- **Brand personality/tone**: How should the interface feel?\n\nIndividual skills may require additional context — check the skill's preparation section for specifics.\n\n**CRITICAL**: You cannot infer this context by reading the codebase. Code tells you what was built, not who it's for or what it should feel like. Only the creator can provide this context.\n\n**Gathering order:**\n1. **Check current instructions (instant)**: If your loaded instructions already contain a **Design Context** section, proceed immediately.\n2. **Check .impeccable.md (fast)**: If not in instructions, read `.impeccable.md` from the project root. If it exists and contains the required context, proceed.\n3. **Run teach-impeccable (REQUIRED)**: If neither source has context, you MUST run /teach-impeccable NOW before doing anything else. Do NOT skip this step. Do NOT attempt to infer context from the codebase instead.\n\n---\n\n## Design Direction\n\nCommit to a BOLD aesthetic direction:\n- **Purpose**: What problem does this interface solve? Who uses it?\n- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.\n- **Constraints**: Technical requirements (framework, performance, accessibility).\n- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?\n\n**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work—the key is intentionality, not intensity.\n\nThen implement working code that is:\n- Production-grade and functional\n- Visually striking and memorable\n- Cohesive with a clear aesthetic point-of-view\n- Meticulously refined in every detail\n\n## Frontend Aesthetics Guidelines\n\n### Typography\n→ *Consult [typography reference](reference/typography.md) for scales, pairing, and loading strategies.*\n\nChoose fonts that are beautiful, unique, and interesting. Pair a distinctive display font with a refined body font.\n\n**DO**: Use a modular type scale with fluid sizing (clamp)\n**DO**: Vary font weights and sizes to create clear visual hierarchy\n**DON'T**: Use overused fonts—Inter, Roboto, Arial, Open Sans, system defaults\n**DON'T**: Use monospace typography as lazy shorthand for \"technical/developer\" vibes\n**DON'T**: Put large icons with rounded corners above every heading—they rarely add value and make sites look templated\n\n### Color & Theme\n→ *Consult [color reference](reference/color-and-contrast.md) for OKLCH, palettes, and dark mode.*\n\nCommit to a cohesive palette. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.\n\n**DO**: Use modern CSS color functions (oklch, color-mix, light-dark) for perceptually uniform, maintainable palettes\n**DO**: Tint your neutrals toward your brand hue—even a subtle hint creates subconscious cohesion\n**DON'T**: Use gray text on colored backgrounds—it looks washed out; use a shade of the background color instead\n**DON'T**: Use pure black (#000) or pure white (#fff)—always tint; pure black/white never appears in nature\n**DON'T**: Use the AI color palette: cyan-on-dark, purple-to-blue gradients, neon accents on dark backgrounds\n**DON'T**: Use gradient text for \"impact\"—especially on metrics or headings; it's decorative rather than meaningful\n**DON'T**: Default to dark mode with glowing accents—it looks \"cool\" without requiring actual design decisions\n\n### Layout & Space\n→ *Consult [spatial reference](reference/spatial-design.md) for grids, rhythm, and container queries.*\n\nCreate visual rhythm through varied spacing—not the same padding everywhere. Embrace asymmetry and unexpected compositions. Break the grid intentionally for emphasis.\n\n**DO**: Create visual rhythm through varied spacing—tight groupings, generous separations\n**DO**: Use fluid spacing with clamp() that breathes on larger screens\n**DO**: Use asymmetry and unexpected compositions; break the grid intentionally for emphasis\n**DON'T**: Wrap everything in cards—not everything needs a container\n**DON'T**: Nest cards inside cards—visual noise, flatten the hierarchy\n**DON'T**: Use identical card grids—same-sized cards with icon + heading + text, repeated endlessly\n**DON'T**: Use the hero metric layout template—big number, small label, supporting stats, gradient accent\n**DON'T**: Center everything—left-aligned text with asymmetric layouts feels more designed\n**DON'T**: Use the same spacing everywhere—without rhythm, layouts feel monotonous\n\n### Visual Details\n**DO**: Use intentional, purposeful decorative elements that reinforce brand\n**DON'T**: Use glassmorphism everywhere—blur effects, glass cards, glow borders used decoratively rather than purposefully\n**DON'T**: Use rounded elements with thick colored border on one side—a lazy accent that almost never looks intentional\n**DON'T**: Use sparklines as decoration—tiny charts that look sophisticated but convey nothing meaningful\n**DON'T**: Use rounded rectangles with generic drop shadows—safe, forgettable, could be any AI output\n**DON'T**: Use modals unless there's truly no better alternative—modals are lazy\n\n### Motion\n→ *Consult [motion reference](reference/motion-design.md) for timing, easing, and reduced motion.*\n\nFocus on high-impact moments: one well-orchestrated page load with staggered reveals creates more delight than scattered micro-interactions.\n\n**DO**: Use motion to convey state changes—entrances, exits, feedback\n**DO**: Use exponential easing (ease-out-quart/quint/expo) for natural deceleration\n**DO**: For height animations, use grid-template-rows transitions instead of animating height directly\n**DON'T**: Animate layout properties (width, height, padding, margin)—use transform and opacity only\n**DON'T**: Use bounce or elastic easing—they feel dated and tacky; real objects decelerate smoothly\n\n### Interaction\n→ *Consult [interaction reference](reference/interaction-design.md) for forms, focus, and loading patterns.*\n\nMake interactions feel fast. Use optimistic UI—update immediately, sync later.\n\n**DO**: Use progressive disclosure—start simple, reveal sophistication through interaction (basic options first, advanced behind expandable sections; hover states that reveal secondary actions)\n**DO**: Design empty states that teach the interface, not just say \"nothing here\"\n**DO**: Make every interactive surface feel intentional and responsive\n**DON'T**: Repeat the same information—redundant headers, intros that restate the heading\n**DON'T**: Make every button primary—use ghost buttons, text links, secondary styles; hierarchy matters\n\n### Responsive\n→ *Consult [responsive reference](reference/responsive-design.md) for mobile-first, fluid design, and container queries.*\n\n**DO**: Use container queries (@container) for component-level responsiveness\n**DO**: Adapt the interface for different contexts—don't just shrink it\n**DON'T**: Hide critical functionality on mobile—adapt the interface, don't amputate it\n\n### UX Writing\n→ *Consult [ux-writing reference](reference/ux-writing.md) for labels, errors, and empty states.*\n\n**DO**: Make every word earn its place\n**DON'T**: Repeat information users can already see\n\n---\n\n## The AI Slop Test\n\n**Critical quality check**: If you showed this interface to someone and said \"AI made this,\" would they believe you immediately? If yes, that's the problem.\n\nA distinctive interface should make someone ask \"how was this made?\" not \"which AI made this?\"\n\nReview the DON'T guidelines above—they are the fingerprints of AI-generated work from 2024-2025.\n\n---\n\n## Implementation Principles\n\nMatch implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details.\n\nInterpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices across generations.\n\nRemember: the model is capable of extraordinary creative work. Don't hold back—show what can truly be created when thinking outside the box and committing fully to a distinctive vision."}],"isError":false,"timestamp":1775941185214}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":5554,"output":19,"cacheRead":0,"cacheWrite":0,"totalTokens":5573,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"},"toolResults":[{"role":"toolResult","toolCallId":"call_UzN6ivG1lG5v82d7bFgDFU4M","toolName":"read","content":[{"type":"text","text":"---\nname: frontend-design\ndescription: Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.\nlicense: Apache 2.0. Based on Anthropic's frontend-design skill. See NOTICE.md for attribution.\n---\n\nThis skill guides creation of distinctive, production-grade frontend interfaces that avoid generic \"AI slop\" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.\n\n## Context Gathering Protocol\n\nDesign skills produce generic output without project context. You MUST have confirmed design context before doing any design work.\n\n**Required context** — every design skill needs at minimum:\n- **Target audience**: Who uses this product and in what context?\n- **Use cases**: What jobs are they trying to get done?\n- **Brand personality/tone**: How should the interface feel?\n\nIndividual skills may require additional context — check the skill's preparation section for specifics.\n\n**CRITICAL**: You cannot infer this context by reading the codebase. Code tells you what was built, not who it's for or what it should feel like. Only the creator can provide this context.\n\n**Gathering order:**\n1. **Check current instructions (instant)**: If your loaded instructions already contain a **Design Context** section, proceed immediately.\n2. **Check .impeccable.md (fast)**: If not in instructions, read `.impeccable.md` from the project root. If it exists and contains the required context, proceed.\n3. **Run teach-impeccable (REQUIRED)**: If neither source has context, you MUST run /teach-impeccable NOW before doing anything else. Do NOT skip this step. Do NOT attempt to infer context from the codebase instead.\n\n---\n\n## Design Direction\n\nCommit to a BOLD aesthetic direction:\n- **Purpose**: What problem does this interface solve? Who uses it?\n- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.\n- **Constraints**: Technical requirements (framework, performance, accessibility).\n- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?\n\n**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work—the key is intentionality, not intensity.\n\nThen implement working code that is:\n- Production-grade and functional\n- Visually striking and memorable\n- Cohesive with a clear aesthetic point-of-view\n- Meticulously refined in every detail\n\n## Frontend Aesthetics Guidelines\n\n### Typography\n→ *Consult [typography reference](reference/typography.md) for scales, pairing, and loading strategies.*\n\nChoose fonts that are beautiful, unique, and interesting. Pair a distinctive display font with a refined body font.\n\n**DO**: Use a modular type scale with fluid sizing (clamp)\n**DO**: Vary font weights and sizes to create clear visual hierarchy\n**DON'T**: Use overused fonts—Inter, Roboto, Arial, Open Sans, system defaults\n**DON'T**: Use monospace typography as lazy shorthand for \"technical/developer\" vibes\n**DON'T**: Put large icons with rounded corners above every heading—they rarely add value and make sites look templated\n\n### Color & Theme\n→ *Consult [color reference](reference/color-and-contrast.md) for OKLCH, palettes, and dark mode.*\n\nCommit to a cohesive palette. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.\n\n**DO**: Use modern CSS color functions (oklch, color-mix, light-dark) for perceptually uniform, maintainable palettes\n**DO**: Tint your neutrals toward your brand hue—even a subtle hint creates subconscious cohesion\n**DON'T**: Use gray text on colored backgrounds—it looks washed out; use a shade of the background color instead\n**DON'T**: Use pure black (#000) or pure white (#fff)—always tint; pure black/white never appears in nature\n**DON'T**: Use the AI color palette: cyan-on-dark, purple-to-blue gradients, neon accents on dark backgrounds\n**DON'T**: Use gradient text for \"impact\"—especially on metrics or headings; it's decorative rather than meaningful\n**DON'T**: Default to dark mode with glowing accents—it looks \"cool\" without requiring actual design decisions\n\n### Layout & Space\n→ *Consult [spatial reference](reference/spatial-design.md) for grids, rhythm, and container queries.*\n\nCreate visual rhythm through varied spacing—not the same padding everywhere. Embrace asymmetry and unexpected compositions. Break the grid intentionally for emphasis.\n\n**DO**: Create visual rhythm through varied spacing—tight groupings, generous separations\n**DO**: Use fluid spacing with clamp() that breathes on larger screens\n**DO**: Use asymmetry and unexpected compositions; break the grid intentionally for emphasis\n**DON'T**: Wrap everything in cards—not everything needs a container\n**DON'T**: Nest cards inside cards—visual noise, flatten the hierarchy\n**DON'T**: Use identical card grids—same-sized cards with icon + heading + text, repeated endlessly\n**DON'T**: Use the hero metric layout template—big number, small label, supporting stats, gradient accent\n**DON'T**: Center everything—left-aligned text with asymmetric layouts feels more designed\n**DON'T**: Use the same spacing everywhere—without rhythm, layouts feel monotonous\n\n### Visual Details\n**DO**: Use intentional, purposeful decorative elements that reinforce brand\n**DON'T**: Use glassmorphism everywhere—blur effects, glass cards, glow borders used decoratively rather than purposefully\n**DON'T**: Use rounded elements with thick colored border on one side—a lazy accent that almost never looks intentional\n**DON'T**: Use sparklines as decoration—tiny charts that look sophisticated but convey nothing meaningful\n**DON'T**: Use rounded rectangles with generic drop shadows—safe, forgettable, could be any AI output\n**DON'T**: Use modals unless there's truly no better alternative—modals are lazy\n\n### Motion\n→ *Consult [motion reference](reference/motion-design.md) for timing, easing, and reduced motion.*\n\nFocus on high-impact moments: one well-orchestrated page load with staggered reveals creates more delight than scattered micro-interactions.\n\n**DO**: Use motion to convey state changes—entrances, exits, feedback\n**DO**: Use exponential easing (ease-out-quart/quint/expo) for natural deceleration\n**DO**: For height animations, use grid-template-rows transitions instead of animating height directly\n**DON'T**: Animate layout properties (width, height, padding, margin)—use transform and opacity only\n**DON'T**: Use bounce or elastic easing—they feel dated and tacky; real objects decelerate smoothly\n\n### Interaction\n→ *Consult [interaction reference](reference/interaction-design.md) for forms, focus, and loading patterns.*\n\nMake interactions feel fast. Use optimistic UI—update immediately, sync later.\n\n**DO**: Use progressive disclosure—start simple, reveal sophistication through interaction (basic options first, advanced behind expandable sections; hover states that reveal secondary actions)\n**DO**: Design empty states that teach the interface, not just say \"nothing here\"\n**DO**: Make every interactive surface feel intentional and responsive\n**DON'T**: Repeat the same information—redundant headers, intros that restate the heading\n**DON'T**: Make every button primary—use ghost buttons, text links, secondary styles; hierarchy matters\n\n### Responsive\n→ *Consult [responsive reference](reference/responsive-design.md) for mobile-first, fluid design, and container queries.*\n\n**DO**: Use container queries (@container) for component-level responsiveness\n**DO**: Adapt the interface for different contexts—don't just shrink it\n**DON'T**: Hide critical functionality on mobile—adapt the interface, don't amputate it\n\n### UX Writing\n→ *Consult [ux-writing reference](reference/ux-writing.md) for labels, errors, and empty states.*\n\n**DO**: Make every word earn its place\n**DON'T**: Repeat information users can already see\n\n---\n\n## The AI Slop Test\n\n**Critical quality check**: If you showed this interface to someone and said \"AI made this,\" would they believe you immediately? If yes, that's the problem.\n\nA distinctive interface should make someone ask \"how was this made?\" not \"which AI made this?\"\n\nReview the DON'T guidelines above—they are the fingerprints of AI-generated work from 2024-2025.\n\n---\n\n## Implementation Principles\n\nMatch implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details.\n\nInterpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices across generations.\n\nRemember: the model is capable of extraordinary creative work. Don't hold back—show what can truly be created when thinking outside the box and committing fully to a distinctive vision."}],"isError":false,"timestamp":1775941185214}]}
{"type":"turn_start"}
{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222}}
{"type":"message_update","assistantMessageEvent":{"type":"text_start","contentIndex":0,"partial":{"role":"assistant","content":[{"type":"text","text":"Skills"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"Skills","partial":{"role":"assistant","content":[{"type":"text","text":"Skills"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"text","text":"Skills:"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills:"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" extract","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract,"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract,"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" audit","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":",","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit,"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit,"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" \n","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \n"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \n"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"Order","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder:"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder:"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" frontend","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design →"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design →"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" extract","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" →","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract →"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract →"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" audit","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" \n","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \n"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \n"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"Why","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":":","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy:"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy:"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" Gather","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" ensure","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" design","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" system","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" context","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context ("}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context ("}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"frontend","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"-design","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design),"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design),"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" extract","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" reusable","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" components","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"/t","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/t"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/t"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"okens","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens ("}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens ("}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"extract","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"),","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract),"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract),"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" confirm","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" alignment","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" with","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" anti","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"-pattern","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-pattern"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-pattern"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"s","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" and","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" sl","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and sl"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and sl"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"op","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" test","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" (","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test ("}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test ("}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"audit","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit"}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":").","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_update","assistantMessageEvent":{"type":"text_end","contentIndex":0,"content":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit).","partial":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":6082,"output":53,"cacheRead":2048,"cacheWrite":0,"totalTokens":8183,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}},"message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":6082,"output":53,"cacheRead":2048,"cacheWrite":0,"totalTokens":8183,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"message_end","message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":6082,"output":53,"cacheRead":2048,"cacheWrite":0,"totalTokens":8183,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}}
{"type":"turn_end","message":{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":6082,"output":53,"cacheRead":2048,"cacheWrite":0,"totalTokens":8183,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"},"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. Inspect the skill folders if needed. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ..."}],"timestamp":1775941180130},{"role":"assistant","content":[{"type":"toolCall","id":"call_e1dq160zkaw7nca0GCWWqEXv","name":"bash","arguments":{"command":"ls -1"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":86,"output":17,"cacheRead":2176,"cacheWrite":0,"totalTokens":2279,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941180179,"responseId":"chatcmpl-DTZiXbkcJjUpdSbcvUN35yrzTx8Kx"},{"role":"toolResult","toolCallId":"call_e1dq160zkaw7nca0GCWWqEXv","toolName":"bash","content":[{"type":"text","text":"adapt\nanimate\narrange\naudit\nbolder\nclarify\ncolorize\ncritique\ndelight\ndistill\nextract\nfrontend-design\nharden\nnormalize\nonboard\noptimize\noverdrive\npolish\nquieter\nteach-impeccable\ntypeset\n"}],"isError":false,"timestamp":1775941181609},{"role":"assistant","content":[{"type":"toolCall","id":"call_QyRuYwIQ8eef9WIYrGSc2iid","name":"read","arguments":{"path":"extract/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":170,"output":18,"cacheRead":2176,"cacheWrite":0,"totalTokens":2364,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941181612,"responseId":"chatcmpl-DTZiYK4eJwS69OWLsDvmIKtJPoWj3"},{"role":"toolResult","toolCallId":"call_QyRuYwIQ8eef9WIYrGSc2iid","toolName":"read","content":[{"type":"text","text":"---\nname: extract\ndescription: Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.\n---\n\nIdentify reusable patterns, components, and design tokens, then extract and consolidate them into the design system for systematic reuse.\n\n## Discover\n\nAnalyze the target area to identify extraction opportunities:\n\n1. **Find the design system**: Locate your design system, component library, or shared UI directory (grep for \"design system\", \"ui\", \"components\", etc.). Understand its structure:\n - Component organization and naming conventions\n - Design token structure (if any)\n - Documentation patterns\n - Import/export conventions\n \n **CRITICAL**: If no design system exists, ask before creating one. Understand the preferred location and structure first.\n\n2. **Identify patterns**: Look for:\n - **Repeated components**: Similar UI patterns used multiple times (buttons, cards, inputs, etc.)\n - **Hard-coded values**: Colors, spacing, typography, shadows that should be tokens\n - **Inconsistent variations**: Multiple implementations of the same concept (3 different button styles)\n - **Reusable patterns**: Layout patterns, composition patterns, interaction patterns worth systematizing\n\n3. **Assess value**: Not everything should be extracted. Consider:\n - Is this used 3+ times, or likely to be reused?\n - Would systematizing this improve consistency?\n - Is this a general pattern or context-specific?\n - What's the maintenance cost vs benefit?\n\n## Plan Extraction\n\nCreate a systematic extraction plan:\n\n- **Components to extract**: Which UI elements become reusable components?\n- **Tokens to create**: Which hard-coded values become design tokens?\n- **Variants to support**: What variations does each component need?\n- **Naming conventions**: Component names, token names, prop names that match existing patterns\n- **Migration path**: How to refactor existing uses to consume the new shared versions\n\n**IMPORTANT**: Design systems grow incrementally. Extract what's clearly reusable now, not everything that might someday be reusable.\n\n## Extract & Enrich\n\nBuild improved, reusable versions:\n\n- **Components**: Create well-designed components with:\n - Clear props API with sensible defaults\n - Proper variants for different use cases\n - Accessibility built in (ARIA, keyboard navigation, focus management)\n - Documentation and usage examples\n \n- **Design tokens**: Create tokens with:\n - Clear naming (primitive vs semantic)\n - Proper hierarchy and organization\n - Documentation of when to use each token\n \n- **Patterns**: Document patterns with:\n - When to use this pattern\n - Code examples\n - Variations and combinations\n\n**NEVER**:\n- Extract one-off, context-specific implementations without generalization\n- Create components so generic they're useless\n- Extract without considering existing design system conventions\n- Skip proper TypeScript types or prop documentation\n- Create tokens for every single value (tokens should have semantic meaning)\n\n## Migrate\n\nReplace existing uses with the new shared versions:\n\n- **Find all instances**: Search for the patterns you've extracted\n- **Replace systematically**: Update each use to consume the shared version\n- **Test thoroughly**: Ensure visual and functional parity\n- **Delete dead code**: Remove the old implementations\n\n## Document\n\nUpdate design system documentation:\n\n- Add new components to the component library\n- Document token usage and values\n- Add examples and guidelines\n- Update any Storybook or component catalog\n\nRemember: A good design system is a living system. Extract patterns as they emerge, enrich them thoughtfully, and maintain them consistently."}],"isError":false,"timestamp":1775941182726},{"role":"assistant","content":[{"type":"toolCall","id":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","name":"read","arguments":{"path":"audit/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":1154,"output":18,"cacheRead":2048,"cacheWrite":0,"totalTokens":3220,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941182731,"responseId":"chatcmpl-DTZiZQbARUMpeBtEMisgjeL3Rov1P"},{"role":"toolResult","toolCallId":"call_Fbh6xXyGQSiMeKGMHjPP7NoR","toolName":"read","content":[{"type":"text","text":"---\nname: audit\ndescription: Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.\n---\n\n## MANDATORY PREPARATION\n\nInvoke /frontend-design — it contains design principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.\n\n---\n\nRun systematic **technical** quality checks and generate a comprehensive report. Don't fix issues — document them for other commands to address.\n\nThis is a code-level audit, not a design critique. Check what's measurable and verifiable in the implementation.\n\n## Diagnostic Scan\n\nRun comprehensive checks across 5 dimensions. Score each dimension 0-4 using the criteria below.\n\n### 1. Accessibility (A11y)\n\n**Check for**:\n- **Contrast issues**: Text contrast ratios < 4.5:1 (or 7:1 for AAA)\n- **Missing ARIA**: Interactive elements without proper roles, labels, or states\n- **Keyboard navigation**: Missing focus indicators, illogical tab order, keyboard traps\n- **Semantic HTML**: Improper heading hierarchy, missing landmarks, divs instead of buttons\n- **Alt text**: Missing or poor image descriptions\n- **Form issues**: Inputs without labels, poor error messaging, missing required indicators\n\n**Score 0-4**: 0=Inaccessible (fails WCAG A), 1=Major gaps (few ARIA labels, no keyboard nav), 2=Partial (some a11y effort, significant gaps), 3=Good (WCAG AA mostly met, minor gaps), 4=Excellent (WCAG AA fully met, approaches AAA)\n\n### 2. Performance\n\n**Check for**:\n- **Layout thrashing**: Reading/writing layout properties in loops\n- **Expensive animations**: Animating layout properties (width, height, top, left) instead of transform/opacity\n- **Missing optimization**: Images without lazy loading, unoptimized assets, missing will-change\n- **Bundle size**: Unnecessary imports, unused dependencies\n- **Render performance**: Unnecessary re-renders, missing memoization\n\n**Score 0-4**: 0=Severe issues (layout thrash, unoptimized everything), 1=Major problems (no lazy loading, expensive animations), 2=Partial (some optimization, gaps remain), 3=Good (mostly optimized, minor improvements possible), 4=Excellent (fast, lean, well-optimized)\n\n### 3. Theming\n\n**Check for**:\n- **Hard-coded colors**: Colors not using design tokens\n- **Broken dark mode**: Missing dark mode variants, poor contrast in dark theme\n- **Inconsistent tokens**: Using wrong tokens, mixing token types\n- **Theme switching issues**: Values that don't update on theme change\n\n**Score 0-4**: 0=No theming (hard-coded everything), 1=Minimal tokens (mostly hard-coded), 2=Partial (tokens exist but inconsistently used), 3=Good (tokens used, minor hard-coded values), 4=Excellent (full token system, dark mode works perfectly)\n\n### 4. Responsive Design\n\n**Check for**:\n- **Fixed widths**: Hard-coded widths that break on mobile\n- **Touch targets**: Interactive elements < 44x44px\n- **Horizontal scroll**: Content overflow on narrow viewports\n- **Text scaling**: Layouts that break when text size increases\n- **Missing breakpoints**: No mobile/tablet variants\n\n**Score 0-4**: 0=Desktop-only (breaks on mobile), 1=Major issues (some breakpoints, many failures), 2=Partial (works on mobile, rough edges), 3=Good (responsive, minor touch target or overflow issues), 4=Excellent (fluid, all viewports, proper touch targets)\n\n### 5. Anti-Patterns (CRITICAL)\n\nCheck against ALL the **DON'T** guidelines in the frontend-design skill. Look for AI slop tells (AI color palette, gradient text, glassmorphism, hero metrics, card grids, generic fonts) and general design anti-patterns (gray on color, nested cards, bounce easing, redundant copy).\n\n**Score 0-4**: 0=AI slop gallery (5+ tells), 1=Heavy AI aesthetic (3-4 tells), 2=Some tells (1-2 noticeable), 3=Mostly clean (subtle issues only), 4=No AI tells (distinctive, intentional design)\n\n## Generate Report\n\n### Audit Health Score\n\n| # | Dimension | Score | Key Finding |\n|---|-----------|-------|-------------|\n| 1 | Accessibility | ? | [most critical a11y issue or \"--\"] |\n| 2 | Performance | ? | |\n| 3 | Responsive Design | ? | |\n| 4 | Theming | ? | |\n| 5 | Anti-Patterns | ? | |\n| **Total** | | **??/20** | **[Rating band]** |\n\n**Rating bands**: 18-20 Excellent (minor polish), 14-17 Good (address weak dimensions), 10-13 Acceptable (significant work needed), 6-9 Poor (major overhaul), 0-5 Critical (fundamental issues)\n\n### Anti-Patterns Verdict\n**Start here.** Pass/fail: Does this look AI-generated? List specific tells. Be brutally honest.\n\n### Executive Summary\n- Audit Health Score: **??/20** ([rating band])\n- Total issues found (count by severity: P0/P1/P2/P3)\n- Top 3-5 critical issues\n- Recommended next steps\n\n### Detailed Findings by Severity\n\nTag every issue with **P0-P3 severity**:\n- **P0 Blocking**: Prevents task completion — fix immediately\n- **P1 Major**: Significant difficulty or WCAG AA violation — fix before release\n- **P2 Minor**: Annoyance, workaround exists — fix in next pass\n- **P3 Polish**: Nice-to-fix, no real user impact — fix if time permits\n\nFor each issue, document:\n- **[P?] Issue name**\n- **Location**: Component, file, line\n- **Category**: Accessibility / Performance / Theming / Responsive / Anti-Pattern\n- **Impact**: How it affects users\n- **WCAG/Standard**: Which standard it violates (if applicable)\n- **Recommendation**: How to fix it\n- **Suggested command**: Which command to use (prefer: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive)\n\n### Patterns & Systemic Issues\n\nIdentify recurring problems that indicate systemic gaps rather than one-off mistakes:\n- \"Hard-coded colors appear in 15+ components, should use design tokens\"\n- \"Touch targets consistently too small (<44px) throughout mobile experience\"\n\n### Positive Findings\n\nNote what's working well — good practices to maintain and replicate.\n\n## Recommended Actions\n\nList recommended commands in priority order (P0 first, then P1, then P2):\n\n1. **[P?] `/command-name`** — Brief description (specific context from audit findings)\n2. **[P?] `/command-name`** — Brief description (specific context)\n\n**Rules**: Only recommend commands from: /animate, /quieter, /optimize, /adapt, /clarify, /distill, /delight, /onboard, /normalize, /audit, /harden, /polish, /extract, /bolder, /arrange, /typeset, /critique, /colorize, /overdrive. Map findings to the most appropriate command. End with `/polish` as the final step if any fixes were recommended.\n\nAfter presenting the summary, tell the user:\n\n> You can ask me to run these one at a time, all at once, or in any order you prefer.\n>\n> Re-run `/audit` after fixes to see your score improve.\n\n**IMPORTANT**: Be thorough but actionable. Too many P3 issues creates noise. Focus on what actually matters.\n\n**NEVER**:\n- Report issues without explaining impact (why does this matter?)\n- Provide generic recommendations (be specific and actionable)\n- Skip positive findings (celebrate what works)\n- Forget to prioritize (everything can't be P0)\n- Report false positives without verification\n\nRemember: You're a technical quality auditor. Document systematically, prioritize ruthlessly, cite specific code locations, and provide clear paths to improvement."}],"isError":false,"timestamp":1775941183908},{"role":"assistant","content":[{"type":"toolCall","id":"call_UzN6ivG1lG5v82d7bFgDFU4M","name":"read","arguments":{"path":"frontend-design/SKILL.md"}}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":5554,"output":19,"cacheRead":0,"cacheWrite":0,"totalTokens":5573,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1775941183913,"responseId":"chatcmpl-DTZia3FbKkcxlBF5XluXLkZJ4zZNT"},{"role":"toolResult","toolCallId":"call_UzN6ivG1lG5v82d7bFgDFU4M","toolName":"read","content":[{"type":"text","text":"---\nname: frontend-design\ndescription: Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.\nlicense: Apache 2.0. Based on Anthropic's frontend-design skill. See NOTICE.md for attribution.\n---\n\nThis skill guides creation of distinctive, production-grade frontend interfaces that avoid generic \"AI slop\" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.\n\n## Context Gathering Protocol\n\nDesign skills produce generic output without project context. You MUST have confirmed design context before doing any design work.\n\n**Required context** — every design skill needs at minimum:\n- **Target audience**: Who uses this product and in what context?\n- **Use cases**: What jobs are they trying to get done?\n- **Brand personality/tone**: How should the interface feel?\n\nIndividual skills may require additional context — check the skill's preparation section for specifics.\n\n**CRITICAL**: You cannot infer this context by reading the codebase. Code tells you what was built, not who it's for or what it should feel like. Only the creator can provide this context.\n\n**Gathering order:**\n1. **Check current instructions (instant)**: If your loaded instructions already contain a **Design Context** section, proceed immediately.\n2. **Check .impeccable.md (fast)**: If not in instructions, read `.impeccable.md` from the project root. If it exists and contains the required context, proceed.\n3. **Run teach-impeccable (REQUIRED)**: If neither source has context, you MUST run /teach-impeccable NOW before doing anything else. Do NOT skip this step. Do NOT attempt to infer context from the codebase instead.\n\n---\n\n## Design Direction\n\nCommit to a BOLD aesthetic direction:\n- **Purpose**: What problem does this interface solve? Who uses it?\n- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.\n- **Constraints**: Technical requirements (framework, performance, accessibility).\n- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?\n\n**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work—the key is intentionality, not intensity.\n\nThen implement working code that is:\n- Production-grade and functional\n- Visually striking and memorable\n- Cohesive with a clear aesthetic point-of-view\n- Meticulously refined in every detail\n\n## Frontend Aesthetics Guidelines\n\n### Typography\n→ *Consult [typography reference](reference/typography.md) for scales, pairing, and loading strategies.*\n\nChoose fonts that are beautiful, unique, and interesting. Pair a distinctive display font with a refined body font.\n\n**DO**: Use a modular type scale with fluid sizing (clamp)\n**DO**: Vary font weights and sizes to create clear visual hierarchy\n**DON'T**: Use overused fonts—Inter, Roboto, Arial, Open Sans, system defaults\n**DON'T**: Use monospace typography as lazy shorthand for \"technical/developer\" vibes\n**DON'T**: Put large icons with rounded corners above every heading—they rarely add value and make sites look templated\n\n### Color & Theme\n→ *Consult [color reference](reference/color-and-contrast.md) for OKLCH, palettes, and dark mode.*\n\nCommit to a cohesive palette. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.\n\n**DO**: Use modern CSS color functions (oklch, color-mix, light-dark) for perceptually uniform, maintainable palettes\n**DO**: Tint your neutrals toward your brand hue—even a subtle hint creates subconscious cohesion\n**DON'T**: Use gray text on colored backgrounds—it looks washed out; use a shade of the background color instead\n**DON'T**: Use pure black (#000) or pure white (#fff)—always tint; pure black/white never appears in nature\n**DON'T**: Use the AI color palette: cyan-on-dark, purple-to-blue gradients, neon accents on dark backgrounds\n**DON'T**: Use gradient text for \"impact\"—especially on metrics or headings; it's decorative rather than meaningful\n**DON'T**: Default to dark mode with glowing accents—it looks \"cool\" without requiring actual design decisions\n\n### Layout & Space\n→ *Consult [spatial reference](reference/spatial-design.md) for grids, rhythm, and container queries.*\n\nCreate visual rhythm through varied spacing—not the same padding everywhere. Embrace asymmetry and unexpected compositions. Break the grid intentionally for emphasis.\n\n**DO**: Create visual rhythm through varied spacing—tight groupings, generous separations\n**DO**: Use fluid spacing with clamp() that breathes on larger screens\n**DO**: Use asymmetry and unexpected compositions; break the grid intentionally for emphasis\n**DON'T**: Wrap everything in cards—not everything needs a container\n**DON'T**: Nest cards inside cards—visual noise, flatten the hierarchy\n**DON'T**: Use identical card grids—same-sized cards with icon + heading + text, repeated endlessly\n**DON'T**: Use the hero metric layout template—big number, small label, supporting stats, gradient accent\n**DON'T**: Center everything—left-aligned text with asymmetric layouts feels more designed\n**DON'T**: Use the same spacing everywhere—without rhythm, layouts feel monotonous\n\n### Visual Details\n**DO**: Use intentional, purposeful decorative elements that reinforce brand\n**DON'T**: Use glassmorphism everywhere—blur effects, glass cards, glow borders used decoratively rather than purposefully\n**DON'T**: Use rounded elements with thick colored border on one side—a lazy accent that almost never looks intentional\n**DON'T**: Use sparklines as decoration—tiny charts that look sophisticated but convey nothing meaningful\n**DON'T**: Use rounded rectangles with generic drop shadows—safe, forgettable, could be any AI output\n**DON'T**: Use modals unless there's truly no better alternative—modals are lazy\n\n### Motion\n→ *Consult [motion reference](reference/motion-design.md) for timing, easing, and reduced motion.*\n\nFocus on high-impact moments: one well-orchestrated page load with staggered reveals creates more delight than scattered micro-interactions.\n\n**DO**: Use motion to convey state changes—entrances, exits, feedback\n**DO**: Use exponential easing (ease-out-quart/quint/expo) for natural deceleration\n**DO**: For height animations, use grid-template-rows transitions instead of animating height directly\n**DON'T**: Animate layout properties (width, height, padding, margin)—use transform and opacity only\n**DON'T**: Use bounce or elastic easing—they feel dated and tacky; real objects decelerate smoothly\n\n### Interaction\n→ *Consult [interaction reference](reference/interaction-design.md) for forms, focus, and loading patterns.*\n\nMake interactions feel fast. Use optimistic UI—update immediately, sync later.\n\n**DO**: Use progressive disclosure—start simple, reveal sophistication through interaction (basic options first, advanced behind expandable sections; hover states that reveal secondary actions)\n**DO**: Design empty states that teach the interface, not just say \"nothing here\"\n**DO**: Make every interactive surface feel intentional and responsive\n**DON'T**: Repeat the same information—redundant headers, intros that restate the heading\n**DON'T**: Make every button primary—use ghost buttons, text links, secondary styles; hierarchy matters\n\n### Responsive\n→ *Consult [responsive reference](reference/responsive-design.md) for mobile-first, fluid design, and container queries.*\n\n**DO**: Use container queries (@container) for component-level responsiveness\n**DO**: Adapt the interface for different contexts—don't just shrink it\n**DON'T**: Hide critical functionality on mobile—adapt the interface, don't amputate it\n\n### UX Writing\n→ *Consult [ux-writing reference](reference/ux-writing.md) for labels, errors, and empty states.*\n\n**DO**: Make every word earn its place\n**DON'T**: Repeat information users can already see\n\n---\n\n## The AI Slop Test\n\n**Critical quality check**: If you showed this interface to someone and said \"AI made this,\" would they believe you immediately? If yes, that's the problem.\n\nA distinctive interface should make someone ask \"how was this made?\" not \"which AI made this?\"\n\nReview the DON'T guidelines above—they are the fingerprints of AI-generated work from 2024-2025.\n\n---\n\n## Implementation Principles\n\nMatch implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details.\n\nInterpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices across generations.\n\nRemember: the model is capable of extraordinary creative work. Don't hold back—show what can truly be created when thinking outside the box and committing fully to a distinctive vision."}],"isError":false,"timestamp":1775941185214},{"role":"assistant","content":[{"type":"text","text":"Skills: extract, audit, frontend-design \nOrder: frontend-design → extract → audit \nWhy: Gather and ensure design system context (frontend-design), extract reusable components/tokens (extract), confirm alignment with anti-patterns and slop test (audit)."}],"api":"openai-completions","provider":"github-copilot","model":"gpt-4o","usage":{"input":6082,"output":53,"cacheRead":2048,"cacheWrite":0,"totalTokens":8183,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1775941185222,"responseId":"chatcmpl-DTZib4imJ9TPMgmIYa7WafFbciXcJ"}]}
Reference in New Issue View Git Blame Copy Permalink