20 lines
3.0 KiB
JSON
20 lines
3.0 KiB
JSON
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":776,"output":193,"cacheRead":2176,"cacheWrite":0,"totalTokens":3145,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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{"type":"tool_call","toolName":"find","args":{"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":1000}}
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{"type":"tool_result","toolName":"find","isError":false}
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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":1294,"output":624,"cacheRead":2176,"cacheWrite":0,"totalTokens":4094,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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{"type":"tool_call","toolName":"read","args":{"path":"extract/SKILL.md"}}
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{"type":"tool_result","toolName":"read","isError":false}
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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2113,"output":21,"cacheRead":2816,"cacheWrite":0,"totalTokens":4950,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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{"type":"tool_call","toolName":"read","args":{"path":"normalize/SKILL.md"}}
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{"type":"tool_result","toolName":"read","isError":false}
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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":3080,"output":21,"cacheRead":2816,"cacheWrite":0,"totalTokens":5917,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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{"type":"tool_call","toolName":"read","args":{"path":"audit/SKILL.md"}}
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{"type":"tool_result","toolName":"read","isError":false}
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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":5431,"output":60,"cacheRead":2816,"cacheWrite":0,"totalTokens":8307,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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{"type":"tool_call","toolName":"read","args":{"path":"frontend-design/SKILL.md"}}
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{"type":"tool_result","toolName":"read","isError":false}
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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":6856,"output":169,"cacheRead":3712,"cacheWrite":0,"totalTokens":10737,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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{"type":"tool_call","toolName":"ls","args":{"path":".","limit":500}}
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{"type":"tool_result","toolName":"ls","isError":false}
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{"type":"assistant_text","text":"Skills: frontend-design, extract, normalize\nOrder: frontend-design -> extract -> normalize\nWhy: frontend-design first to gather context (and run /teach-impeccable if missing); extract to consolidate the repeated card pattern into shared components and canonical tokens; normalize to replace hard-coded values, migrate usages, and realign the UI with the design system.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":7101,"output":2806,"cacheRead":3712,"cacheWrite":0,"totalTokens":13619,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
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