Replay Learnings
Like muscle memory for your coding sessions. Find and surface relevant learnings before you start working.
Trigger
Use when starting a new task, saying "what do I know about", "before I start", "replay", or "remind me about".
Workflow
- Extract keywords from the task description (e.g. "auth refactor" →
auth,middleware,refactor). - Search learnings/memory for matching patterns:
grep -i "auth\|middleware".claude/LEARNED.md 2>/dev/null grep -i "auth\|middleware".claude/learning-log.md 2>/dev/null grep -A2 "\[LEARN\]" CLAUDE.md | grep -i "auth\|middleware" - Check session history for similar work — what was the correction rate?
- Surface the top learnings ranked by relevance.
- If no learnings found, suggest starting with the scout agent to explore first.
Output
REPLAY BRIEFING: <task>
=======================
Past learnings (ranked by relevance):
1. [Testing] Always mock external APIs in auth tests (applied 8x)
Mistake: Called live API in tests, caused flaky failures
2. [Navigation] Auth middleware is in src/middleware/ not src/auth/ (applied 5x)
3. [Quality] Add error boundary around auth state changes (applied 3x)
Session history for similar work:
- 2026-02-01: auth refactor — 23 edits, 2 corrections (8.7% rate)
- 2026-01-28: auth middleware — 15 edits, 4 corrections (26.7% rate)
^ Higher correction rate — review patterns before starting
Suggested approach:
- Mock external APIs (learning #1)
- Check src/middleware/ first for auth code (learning #2)Guardrails
- Rank by relevance, not recency.
- Include the original mistake context so the learning is actionable.
- Flag high correction-rate sessions as areas requiring extra care.
- If no learnings match, say so explicitly rather than forcing irrelevant results.