๐Ÿ”—
AI EngineeringPython

LangChain

by davila7

LangChain is an AI Engineering skill for Claude Code, published by davila7 in claude-code-templates.

30.2K stars3.4K forkson davila7/claude-code-templatesAdded 2026/08/14Repository updated 2026/08/14
anthropicanthropic-claudeclaudeclaude-code
Install in seconds
Install LangChain
Copy LangChain 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/davila7/claude-code-templates/tree/main/cli-tool/components/skills/ai-research/agents-langchain ~/.claude/skills/agents-langchain

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

Without Node.js

git clone https://github.com/davila7/claude-code-templates.git

Clones the whole repository, then copy the skillโ€™s own directory into your skills folder yourself.

In this catalog

Source file
cli-tool/components/skills/ai-research/agents-langchain/SKILL.md in davila7/claude-code-templates
Installs to
~/.claude/skills/agents-langchain
Collection
One of 25 skills cataloged from this repository
Category
AI Engineering โ€” 2451 skills

What LangChain does

LangChain is a framework for building LLM-powered applications with agents, chains, and RAG. Use it for chatbots, question-answering systems, autonomous agents, and rapid prototyping across multiple providers.

LangChain is cataloged under AI Engineering on DirSkills. LangChain comes from a repository tagged anthropic, anthropic-claude, claude and claude-code.

Documentation

README

LangChain - Build LLM Applications with Agents & RAG

The most popular framework for building LLM-powered applications.

When to use LangChain

Use LangChain when:

  • Building agents with tool calling and reasoning (ReAct pattern)
  • Implementing RAG (retrieval-augmented generation) pipelines
  • Need to swap LLM providers easily (OpenAI, Anthropic, Google)
  • Creating chatbots with conversation memory
  • Rapid prototyping of LLM applications
  • Production deployments with LangSmith observability

Metrics:

  • 119,000+ GitHub stars
  • 272,000+ repositories use LangChain
  • 500+ integrations (models, vector stores, tools)
  • 3,800+ contributors

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

Frequently asked about LangChain

  • What else does davila7 publish alongside LangChain?

    LangChain is one of 25 skills that DirSkills catalogs from davila7/claude-code-templates, the repository it ships in. Its siblings there include AI Agents Architect, Agent Evaluation and Agent Management. Each one is a separate skill with its own page in this directory, installs the same way LangChain does, and is maintained by davila7 in that same repository. The rest of the collection is listed on the davila7/claude-code-templates page.

  • How does LangChain compare to other AI Engineering skills?

    LangChain ranks #208 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 LangChain against them. Open each page to compare what they document and how they install.

More from davila7/claude-code-templates

LangChain is one of 25 skills cataloged on DirSkills from davila7/claude-code-templates.

See all 25 skills โ†’
๐Ÿค–
2w ago

AI Agents Architect

AI Agents Architect designs and builds autonomous AI agents, covering tool use, memory systems, planning strategies, and multi-agent orchestration. Use it when building or debugging AI agents that need function calling, planning loops, and controlled autonomy.
AI Engineering
30.2K3.4K
๐Ÿงช
2w ago

Agent Evaluation

Agent Evaluation tests and benchmarks LLM agents using behavioral contracts, capability assessments, reliability metrics, and adversarial testing to catch issues before production. Use it when evaluating agent reliability, designing benchmarks, or monitoring production agents.
Quality
30.2K3.4K
๐Ÿค–
2w ago

Agent Management

Agent Management creates, manages, and orchestrates AI agents through the AI Maestro CLI, covering agent lifecycle tasks such as create, hibernate, wake, rename, export/import, and plugin management.
AI Engineering
30.2K3.4K
๐Ÿค–
2w ago

Agent Manager

Agent Manager starts, stops, monitors, and assigns tasks to multiple local CLI agents running in tmux sessions, with cron-friendly scheduling. Use it when you need to run agents in parallel and tail their logs.
Automation
30.2K3.4K
๐Ÿง 
2w ago

Agent Memory MCP

Agent Memory MCP provides a persistent, searchable memory bank for AI agents, exposing MCP tools to search, write, read, and analyze project knowledge. Use it when an agent needs long-term memory synced with project documentation.
AI Engineering
30.2K3.4K
๐Ÿง 
2w ago

Agent Memory Systems

Agent Memory Systems describes architectures for short-term, long-term, and working memory in AI agents, including vector store selection, chunking strategies, and retrieval patterns. Use it when designing or debugging agent memory to prevent retrieval failures that look like intelligence failures.
AI Engineering
30.2K3.4K