langchain-architecture — Skills

What it does

Building autonomous AI agents with tool access

Implementing complex multi-step LLM workflows

Managing conversation memory and state

Integrating LLMs with external data sources and APIs

Creating modular, reusable LLM application components

Implementing document processing pipelines

Building production-grade LLM applications

Build sophisticated LLM applications with LangChain 1.x and LangGraph for agents, memory, and tool integration.

Source

Repository: https://github.com/wshobson/agents

langchain-architecture FAQ

What does the langchain-architecture skill do?

Design LLM applications using LangChain 1.x and LangGraph for agents, memory, and tool integration. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows. Building autonomous AI agents with tool access Implementing complex multi-step LLM workflows

What does langchain-architecture require?

ConversationTokenBufferMemory: Token-based windowing Token usage tracking

How do I install langchain-architecture?

Run: npx -y skills add https://github.com/wshobson/agents --skill langchain-architecture --agent claude-code — the source lives at github.com/wshobson/agents.

Maintain langchain-architecture?

Let people know it's listed here — add the badge (live metrics, light/dark aware) or a plain link to your README or docs.

[![langchain-architecture on getagentictools](https://getagentictools.com/badge/skills/wshobson-agents-langchain-architecture.svg)](https://getagentictools.com/skills/wshobson-agents-langchain-architecture?ref=badge)

npx agentictools info skills/wshobson-agents-langchain-architecture

The second line is the CLI lookup for this page — handy in READMEs and docs.