=== subagent ===
Agent: scout
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: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/child-session.jsonl
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(no assistant text)
→ find {"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":1000}
✓ find done
(no assistant text)
→ read {"path":"extract/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"normalize/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"audit/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"frontend-design/SKILL.md"}
✓ read done
(no assistant text)
→ ls {"path":".","limit":500}
✓ ls done
Skills: frontend-design, extract, normalize
Order: frontend-design -> extract -> normalize
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.
