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agents-langchain SKILL.md skillA

agents-langchain from davila7/claude-code-templates is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned

mdr add davila7/claude-code-templates/agents-langchain@v1.0.0

Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.

Audit grade: A, 17 of 17 checks passed
Kind: SKILL.md skill
Repository: davila7/claude-code-templates
Path: cli-tool/components/skills/ai-research/agents-langchain/SKILL.md
Versions recorded: 3
Latest version: v1.0.0, committed Oct 26, 2026
First version recorded: Jan 8, 2026
Size: 12,864 bytes
Repository stars: 33,152
License: MIT

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 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**

**Use alternatives instead**:
- **LlamaIndex**: RAG-focused, better for document Q&A
- **LangGraph**: Complex stateful workflows, more control
- **Haystack**: Production search pipelines
- **Semantic Kernel**: Microsoft ecosystem

## Quick start

### Installation

```bash
# Core library (Python 3.10+)
pip install -U langchain

# With OpenAI
pip install langchain-openai

# With Anthropic
pip install langchain-anthropic

# Common extras
pip install langchain-community  # 500+ integrations
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint

mdr add davila7/claude-code-templates/agents-langchain@sha256:3598d6853ed680c5

The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

[![mdr](https://markdownregistry.com/badge/art_nd2hdxyst2nq4zbk.svg)](https://markdownregistry.com/a/art_nd2hdxyst2nq4zbk)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 3 versions of this file, between Jan 8, 2026 and Oct 26, 2026, about one every 145 days.

version	committed	commit	size	audit
v1.0.0 latest	2026-10-26	542e625	12,864 B	A	view · diff
v1.0.0	2026-10-24	13da94c	12,857 B	A	view · diff
v1.0.0	2026-01-08	d9d759e	12,839 B	A	view

Audit of the latest version

A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.

pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (12864 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag

Source

GitHub

davila7/claude-code-templates · 33,152 stars · license MIT · pushed 2026-11-06 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_nd2hdxyst2nq4zbk
GET https://markdownregistry.com/api/v1/resolve?ref=davila7/claude-code-templates/agents-langchain
GET https://markdownregistry.com/api/v1/blob/3598d6853ed680c570b43d5fb921e151f711f76f1bef63dd109d5dda882dcebc

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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