Skip to content
Get packs

LangChain & LangGraph Architecture

Guides the agent in designing LLM apps and agents with LangChain 1.x and LangGraph

Source Download skill
Repository
wshobson/agents
Stars
42,095
Licence
MIT
Files
2 files

What it does

When installed, the agent gets guidance for building LLM-powered applications with LangChain 1.x and LangGraph, covering agent patterns like ReAct and multi-agent supervisors, state management, memory options, document loading and retrieval, and tracing. It can then write code using these libraries, such as a sample agent with search and calculator tools, memory persistence, tests, and Redis caching. The skill is reference guidance for the agent; it does not itself run anything.

Great for

  • Developers building Python applications that call Claude or other LLMs with tools or agents
  • Teams prototyping multi-step LLM workflows or retrieval pipelines in LangChain
  • Engineers who want a starting structure for LangGraph agents with checkpointed memory

Skip it if

  • Non-programmers wanting a finished app: it produces code that still needs setup, keys and review
  • Projects not using LangChain or LangGraph, where the guidance may not match their libraries
  • Production systems without review: the examples are illustrative, and the memory and caching snippets need hardening (e.g., the sample uses in-memory storage and a placeholder database tool)

Try asking

  • “Design a LangGraph agent with a database search tool and conversation memory for my support app”
  • “Show me how to build a ReAct agent with Claude that uses a safe calculator tool”
  • “Set up a document ingestion pipeline with text splitting and a vector store retriever”
  • “Add Redis caching to my LangChain LLM calls and explain the tradeoffs”
Step-by-step guide: how to use LangChain & LangGraph ArchitectureInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 2 original files, the MIT licence and an attribution note.

    langchain-architecture.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip langchain-architecture.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip langchain-architecture.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Name your framework version and provider (e.g., LangChain 1.2 with Anthropic) so the agent picks matching imports
  • Ask for a review of generated code before running it, especially tool functions and any database access
  • Mention whether you need short-term memory, long-term memory, or both so the agent chooses the right checkpointer or memory type

What's inside

  • references/details.md
  • SKILL.md

Redistributed unmodified from wshobson/agents under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.