replay-learnings
Surface past learnings relevant to the current task before starting work. Searches correction history, recalls past mistakes, and applies prior patterns. Use when starting a task, saying "what do I know about", "previous mistakes", "lessons learned", or "remind me about".
Best use case
replay-learnings is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Surface past learnings relevant to the current task before starting work. Searches correction history, recalls past mistakes, and applies prior patterns. Use when starting a task, saying "what do I know about", "previous mistakes", "lessons learned", or "remind me about".
Teams using replay-learnings should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/replay-learnings/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How replay-learnings Compares
| Feature / Agent | replay-learnings | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Surface past learnings relevant to the current task before starting work. Searches correction history, recalls past mistakes, and applies prior patterns. Use when starting a task, saying "what do I know about", "previous mistakes", "lessons learned", or "remind me about".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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
1. Extract keywords from the task description (e.g. "auth refactor" → `auth`, `middleware`, `refactor`).
2. Search learnings/memory for matching patterns:
```bash
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"
```
3. Check session history for similar work — what was the correction rate?
4. Surface the top learnings ranked by relevance.
5. 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.Related Skills
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