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From pro-workflow
Searches past learnings, mistakes, and correction history to surface relevant patterns before starting a task. Helps avoid repeated errors and apply prior insights.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pro-workflow:replay-learningsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Like muscle memory for your coding sessions. Find and surface relevant learnings before you start working.
Like muscle memory for your coding sessions. Find and surface relevant learnings before you start working.
Use when starting a new task, saying "what do I know about", "before I start", "replay", or "remind me about".
auth, middleware, refactor).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"
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)
npx claudepluginhub rohitg00/pro-workflow --plugin pro-workflowRetrieves patterns and lessons from past sessions to reuse fixes, avoid mistakes, and recover context after compaction.
Captures agent mistakes, corrections, and discovered gotchas so they are not repeated. Use when: (1) a command or operation fails unexpectedly, (2) the user corrects the agent, (3) the agent discovers non-obvious behavior through debugging, (4) an API or tool behaves differently than expected, (5) a better approach is found for a recurring task. Also searches past learnings before starting tasks to avoid known pitfalls. Activate alongside the memory skill — they share sage-memory but serve different purposes (memory = codebase knowledge, self-learning = agent mistakes and gotchas). Also trigger on "sage review" or "review learnings" to curate and improve the learning database.
Logs errors, user corrections, missing features, API failures, knowledge gaps, and best practices to .learnings/ markdown files. Promotes key insights to CLAUDE.md and AGENTS.md for AI agent self-improvement.