Agent-Skills.md

Agent Skills: LangChain Documentation

Local LangChain AI documentation reference. Use when asked about LangChain, LangGraph, agents, chains, prompts, memory, tools, retrieval, RAG, vector stores, document loaders, or building LLM applications.

UncategorizedID: jokejason/local-context7/langchain-docs

Repository

jokejason/local-context7
jasonz-ncc42License: MIT
6

Install this agent skill to your local

pnpm dlx add-skill https://github.com/jasonz-ncc42/local-context7/tree/HEAD/dotfiles/codex/skills/langchain-docs

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dotfiles/codex/skills/langchain-docs/SKILL.md

Skill Metadata

Name
langchain-docs
Description
Local LangChain AI documentation reference. Use when asked about LangChain, LangGraph, agents, chains, prompts, memory, tools, retrieval, RAG, vector stores, document loaders, or building LLM applications.

LangChain Documentation

LangChain is a framework for building LLM-powered applications. It provides components for chains, agents, RAG, memory, and tools. LangGraph extends this with stateful multi-agent orchestration.

Navigation Guide

LangChain: references/langchain/ - Core framework docs (51 files)

  • Agents, chains, RAG, memory, tools, models, guardrails
  • Key files: overview.mdx, agents.mdx, knowledge-base.mdx

LangGraph: references/langgraph/ - Multi-agent orchestration (35 files)

  • Graph API, memory, interrupts, durable execution
  • Key files: graph-api.mdx, memory.mdx, agentic-rag.mdx

Python SDK: references/python/ - Python API reference (1283 files)

  • Complete API docs for langchain-core, langchain, langgraph

JavaScript SDK: references/javascript/ - JS/TS API reference (299 files)

  • Complete API docs for @langchain/core, langchain, langgraph

Concepts: references/concepts/ - Foundational concepts (2 files)

Deep Agents: references/deepagents/ - Advanced agent patterns (10 files)

Key Entry Points

| Task | Start Here | |------|------------| | Getting started | references/learn.mdx | | LangChain overview | references/langchain/overview.mdx | | Build an agent | references/langchain/agents.mdx | | RAG implementation | references/langchain/knowledge-base.mdx | | LangGraph intro | references/langgraph/graph-api.mdx | | Memory & state | references/langgraph/memory.mdx | | Python API | references/python/ | | JavaScript API | references/javascript/ |

When to use

Use this skill when the user asks about:

  • LangChain chains, agents, or components
  • LangGraph multi-agent orchestration
  • RAG (Retrieval Augmented Generation)
  • Memory and conversation history
  • Tools and tool calling
  • Vector stores and embeddings
  • Building LLM applications

How to find information

  1. First, read references/STRUCTURE.md to see all 1688 documentation files organized by directory
  2. Use Navigation Guide to find the section
  3. Check Key Entry Points for common tasks
  4. For API details: references/python/ or references/javascript/

STRUCTURE.md contains a complete file listing - always check it first when searching for specific topics.