RAG

by nimadorostkar

RAG is an AI Engineering skill for Claude Code, published by nimadorostkar in Claude-Skills-collection.

18 stars2 forkson nimadorostkar/Claude-Skills-collectionAdded 2026/07/16+13% in starsRepository updated 2026/07/14

View source on GitHub Download repo ZIP

aiclaudeclaude-skillsskills

Install in seconds

Install RAG

Copy RAG 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/nimadorostkar/Claude-Skills-collection/tree/main/skills/ai/rag ~/.claude/skills/rag

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/nimadorostkar/Claude-Skills-collection.git

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

In this catalog

Source file: skills/ai/rag/SKILL.md in nimadorostkar/Claude-Skills-collection
Installs to: ~/.claude/skills/rag
Collection: One of 50 skills cataloged from this repository
Category: AI Engineering — 3670 skills

What RAG does

Use when building retrieval-augmented generation. Covers chunking, embedding and hybrid search, reranking, grounding and citation, and diagnosing whether a bad answer is a retrieval failure or a generation failure.

RAG is cataloged under AI Engineering on DirSkills. RAG comes from a repository tagged ai, claude, claude-skills and skills.

Documentation

README

Excerpt

Building question answering over a document corpus.
A RAG system that returns confident, wrong answers.
Choosing chunking, embedding, and retrieval strategy.
Adding citation and grounding to a generative feature.

Capabilities

Chunking strategies and their trade-offs.
Embedding selection and hybrid (dense + sparse) retrieval.
Reranking and query rewriting.
Grounding, citation, and refusal when evidence is absent.
Component-wise evaluation.

Inputs

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

Frequently asked about RAG

What else does nimadorostkar publish alongside RAG?
RAG is one of 50 skills that DirSkills catalogs from nimadorostkar/Claude-Skills-collection, the repository it ships in. Its siblings there include API Design, Agent Design and Agent Instructions. Each one is a separate skill with its own page in this directory, installs the same way RAG does, and is maintained by nimadorostkar in that same repository. The rest of the collection is listed on the nimadorostkar/Claude-Skills-collection page.
How does RAG compare to other AI Engineering skills?
RAG ranks #3601 by stars among the 3670 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 against them. Open each page to compare what they document and how they install.