RAG Code Review

RAG Code Review is an AI Engineering skill for Claude Code, published by lyonzin in knowledge-rag.

265 stars38 forkson lyonzin/knowledge-ragAdded 2026/09/02+2% in starsRepository updated 2026/09/01

antigravityclaudeclaude-codeclaude-code-clicodexcursor-aidocument-searchhybrid-searchinteligencia-artificialknowledge-baselocal-aimcpmcp-serverragrag-chatbotrag-pipelinererankingretrieval-augmented-generationsemantic-searchvector-database

Install in seconds

Install RAG Code Review

Copy RAG Code Review 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/lyonzin/knowledge-rag/tree/master/skills/workflow/rag-code-review ~/.claude/skills/rag-code-review

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/lyonzin/knowledge-rag.git

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

In this catalog

Source file: skills/workflow/rag-code-review/SKILL.md in lyonzin/knowledge-rag
Installs to: ~/.claude/skills/rag-code-review
Collection: One of 10 skills cataloged from this repository
Category: AI Engineering — 2631 skills

What RAG Code Review does

RAG Code Review consults related ADRs, standards, similar files, and prior incidents before commenting on a code change. Use it for PR reviews or any critique of a diff so feedback is grounded in the team’s own decisions.

RAG Code Review is cataloged under AI Engineering on DirSkills. RAG Code Review comes from a repository tagged antigravity, claude, claude-code, claude-code-cli and codex.

Documentation

README

Excerpt

rag-code-review — review against team standards, not the internet

When to use this skill

Trigger when the user asks:

"Review this PR / code / diff"
"Any issues with this?"
"Does this look right?"
"Is this idiomatic?"
"Should I merge this?"
Any critique-style prompt on a code artifact

What this skill commits to

Before offering ANY review comment, the agent consults the corpus for:

ADRs governing the area (auth, retries, error handling, naming, dependencies…)
Existing patterns — similar files that show the "how we do this" convention
Prior incidents touching the code being changed

Review comments then read as "per ADR-XXXX we do Y here" rather than "generally you should Z".

Steps

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

Frequently asked about RAG Code Review

What else does lyonzin publish alongside RAG Code Review?
RAG Code Review is one of 10 skills that DirSkills catalogs from lyonzin/knowledge-rag, the repository it ships in. Its siblings there include RAG Check First, RAG Evaluate Quality and RAG Index Decisions. Each one is a separate skill with its own page in this directory, installs the same way RAG Code Review does, and is maintained by lyonzin in that same repository. The rest of the collection is listed on the lyonzin/knowledge-rag page.
How does RAG Code Review compare to other AI Engineering skills?
RAG Code Review ranks #2238 by stars among the 2631 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 RAG Code Review against them. Open each page to compare what they document and how they install.