Agent skill · AI & Agents

langchain-rag

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill langchain-rag-coralshades-acm-ai --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 14 KB
Bundled scripts: none
Path: skills/ai-llm/langchain-rag-coralshades-acm-ai/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

<overview> Retrieval Augmented Generation (RAG) enhances LLM responses by fetching relevant context from external knowledge sources. **Pipeline:** 1. **Index**: Load → Split → Embed → Store 2. **Retrieve**: Query → Embed → Search → Return docs 3. **Generate**: Docs + Query → LLM → Response **Key Components:** - **Document Loaders**: Ingest data from files, web, databases - **Text Splitters**: Break documents into chunks - **Embeddings**: Convert text to vectors - **Vector Stores**: Store and search embeddings </overview> <vectorstore-selection> | Vector Store | Use Case | Persistence | |--------------|----------|-------------| | **InMemory** | Testing | Memory only | | **FAISS** | Local, high performance | Disk | | **Chroma** | Development | Disk | | **Pinecone** | Production, managed | Cloud | </vectorstore-selection> --- ## Complete RAG Pipeline <ex-basic-rag-setup> <python> End-to-end RAG pipeline: load documents, split into chunks, embed, store, retrieve, and generate a response. ```python from langchain_openai import ChatOpenAI, OpenAIEmbeddings from langchain_community.vectorstores import InMemoryVectorStore from langchain_text_splitters import RecursiveCharacterTextSplitter

What's inside
Steps it walks through
  1. Complete RAG Pipeline
  2. Document Loaders
  3. Text Splitting
  4. Vector Stores
  5. Retrieval
  6. What You CAN Configure
  7. What You CANNOT Configure
Ships with 1 file
  • metadata.json
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About this skill
What does the langchain-rag skill do?

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill langchain-rag-coralshades-acm-ai --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going