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AI EngineeringJavaScript

Replay Learnings

Replay Learnings is an AI Engineering skill for Claude Code, published by rohitg00 in pro-workflow.

2.8K stars270 forkson rohitg00/pro-workflowAdded 2026/08/17Repository updated 2026/08/10

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Install in seconds

Install Replay Learnings

Copy Replay Learnings into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/rohitg00/pro-workflow/tree/main/skills/replay-learnings ~/.claude/skills/replay-learnings

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/rohitg00/pro-workflow.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/replay-learnings/SKILL.md in rohitg00/pro-workflow
Installs to: ~/.claude/skills/replay-learnings
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Replay Learnings does

Replay Learnings surfaces relevant past mistakes and applied patterns before starting a coding task. It searches correction history and session logs to flag high-risk areas and suggest proven approaches.

Replay Learnings is cataloged under AI Engineering on DirSkills. Replay Learnings comes from a repository tagged agent-orchestration, ai-agents, ai-coding, ai-workflow and claude.

Documentation

README

Excerpt

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

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Replay Learnings

What else does rohitg00 publish alongside Replay Learnings?
Replay Learnings is one of 25 skills that DirSkills catalogs from rohitg00/pro-workflow, the repository it ships in. Its siblings there include Agent Teams, Auto Setup and Batch Orchestration. Each one is a separate skill with its own page in this directory, installs the same way Replay Learnings does, and is maintained by rohitg00 in that same repository. The rest of the collection is listed on the rohitg00/pro-workflow page.
How does Replay Learnings compare to other AI Engineering skills?
Replay Learnings ranks #743 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Replay Learnings against them. Open each page to compare what they document and how they install.

More from rohitg00/pro-workflow

Replay Learnings is one of 25 skills cataloged on DirSkills from rohitg00/pro-workflow.

See all 25 skills →

Agent Teams

Agent Teams coordinates multiple Claude Code sessions as a team with shared task lists, mailbox messaging, and file-lock claiming. Use it to parallelize work on non-overlapping files or delegate cross-layer changes across a lead and teammates.

Auto Setup

Auto Setup detects the project type and configures quality gates, hooks, and settings for a new codebase. Use it when onboarding a new project or setting up CI integration.

Batch Orchestration

Batch Orchestration decomposes large-scale, repetitive code changes into independent units and spawns parallel agents in isolated worktrees to implement them. Use it for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.

Bug Capture

Bug Capture turns a user-reported defect into a durable GitHub issue written in the project's own domain language, without exposing file paths or line numbers. Use it when a user reports a bug conversationally, runs a QA pass, or asks to file an issue.

Compact Guard

Compact Guard preserves critical context state before compaction and restores it after, so an agent can resume work without losing task progress, decisions, or next steps.

Context Engineering

Context Engineering helps you manage context windows in AI coding sessions by mastering four operations: Write, Select, Compress, and Isolate. Use it to keep token budgets efficient, plan compaction strategies, and partition work across subagents and worktrees.

More AI Engineering skills

Replay Learnings is one of 2451 AI Engineering skills cataloged on DirSkills, ranked #743 by stars among them.

Browse all AI Engineering skills →

Architecture Decision Records

Architecture Decision Records captures architectural decisions made during Claude Code sessions as structured ADRs, recording context, alternatives, and rationale. Use it when significant technical choices are made so future developers understand why the codebase is shaped the way it is.

AI-First Engineering

AI-First Engineering defines process, review, and architecture standards for teams where AI agents produce most implementation output. Use it to set ownership rules, quality gates, and evaluation criteria for agent-generated code.

Agentic OS

Agentic OS codifies a persistent multi-agent operating system architecture for Claude Code. Use it when building a multi-agent workflow with file-based memory, slash commands, and scheduled automation that survives session restarts.