30 lines
1.5 KiB
Plaintext
30 lines
1.5 KiB
Plaintext
=== subagent ===
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Agent: scout
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Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "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: ...
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CWD: /home/alex/.pi/agent/skills/frontend
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Requested model: github-copilot/gpt-5-mini
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Resolved model: github-copilot/gpt-5-mini
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Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/child-session.jsonl
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---------------------
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(no assistant text)
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→ find {"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":1000}
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✓ find done
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(no assistant text)
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→ read {"path":"extract/SKILL.md"}
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✓ read done
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(no assistant text)
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→ read {"path":"normalize/SKILL.md"}
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✓ read done
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(no assistant text)
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→ read {"path":"audit/SKILL.md"}
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✓ read done
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(no assistant text)
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→ read {"path":"frontend-design/SKILL.md"}
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✓ read done
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(no assistant text)
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→ ls {"path":".","limit":500}
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✓ ls done
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Skills: frontend-design, extract, normalize
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Order: frontend-design -> extract -> normalize
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Why: 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.
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