mcpField
R
replay-learnings

replay-learnings

github.com/rohitg00Agent workflows2.9k167 installsUpdated 4w ago
Repository

About replay-learnings

A skill for surfacing relevant past learnings before a coding task begins. It searches project memory and session history, ranks matches by relevance, and includes prior mistake context to make the guidance actionable.

Key features

  1. 01Extract keywords from task descriptions
  2. 02Search project learning files
  3. 03Check similar session history
  4. 04Rank learnings by relevance
  5. 05Include context behind past mistakes

Use cases

  1. 01Reviewing prior guidance before a task
  2. 02Preparing for a familiar refactor
  3. 03Finding recurring pitfalls in related work
  4. 04Checking correction patterns from similar sessions

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/rohitg00/pro-workflow --skill replay-learnings

After installing, type/replay-learningsin Claude Code to confirm it loaded.

Details

From the project README

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: 
    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.

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