Mmcp.market

replay-learnings skill

by rohitg00·rohitg00/pro-workflow·2.9k stars

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".

A100/100content scan

Is the replay-learnings skill safe?

Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-09-28.

No findings.

Install the replay-learnings skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/rohitg00/pro-workflow.git /tmp/pro-workflow
mkdir -p ~/.claude/skills
cp -r /tmp/pro-workflow/skills/replay-learnings ~/.claude/skills/replay-learnings
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

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"
  1. Check session history for similar work — what was the correction rate?
  2. Surface the top learnings ranked by relevance.
  3. 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.

More skills from rohitg00/pro-workflow

  • Aagent-teamsCoordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.
  • Aauto-setupAuto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.
  • Abatch-orchestrationDecompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.
  • Cbug-captureCapture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
  • Acompact-guardSmart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.
  • Acontext-engineeringMaster the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
  • Acontext-optimizerOptimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.
  • Acost-trackerTrack session costs, set budget alerts, and optimize token spend. Use to check costs mid-session or set spending limits.
  • Adesign-engineeringApply interface craft when building or reviewing UI - motion, easing, timing, springs, component feel, and visual foundations. Use when building a component, animation, transition, hover or press state, modal, drawer, toast, or when polishing an interface so it feels right. Says "make this feel better", "add an animation", "polish the UI", "review this component".
  • AdeslopRemove AI-generated code slop, unnecessary comments, and over-engineering from the current branch diff. Cleans up boilerplate, simplifies abstractions, strips defensive code, and in skill-file mode lints SKILL.md files for quality. Use when cleaning up code, simplifying, removing boilerplate, before committing, or when reviewing a skill before promoting it.
  • Adomain-modelingBuild the project's shared language and bounded contexts before writing code, so names stay consistent and the agent stops paraphrasing domain concepts. Produces a CONTEXT.md glossary and decision records. Use at the start of a project or feature, or when the codebase and the people describing it speak different languages.
  • Afile-watcherConfigure file watching hooks to auto-react to config changes, env file updates, and dependency modifications. Use to set up reactive workflows.

All agent skills → · MCP servers