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langchain-ai/langgraph-fundamentals

INVOCA ESTA HABILIDAD al escribir CUALQUIER código de LangGraph. Cubre StateGraph, esquemas de estado, nodos, aristas, Command, Send, invocar, transmisión y manejo de errores.

¿Qué es langgraph-fundamentals?

Esta habilidad es esencial para desarrolladores que trabajan con LangGraph, un marco de trabajo para construir agentes de IA y flujos de trabajo de grafo de estado. Proporciona una guía completa sobre los fundamentos de LangGraph, incluyendo StateGraph, esquemas de estado, nodos, aristas, y mecanismos avanzados como Command y Send. Está diseñada para ayudarte a entender cómo invocar y transmitir datos entre nodos, así como manejar errores de manera eficiente. Compatible con plataformas como Claude Code, Cursor y Codex, esta habilidad te permitirá escribir código LangGraph más robusto y escalable, siguiendo las mejores prácticas documentadas.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langgraph-fundamentals

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Documentación

¿Qué hace langgraph-fundamentals?

INVOCA ESTA HABILIDAD al escribir CUALQUIER código de LangGraph. Cubre StateGraph, esquemas de estado, nodos, aristas, Command, Send, invocar, transmisión y manejo de errores.

Individual skills in this repo

This repo contains 11 individual skills — each has its own dedicated page.

langchain-ai/deep-agents-core

INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.

langchain-ai/deep-agents-memory

INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.

langchain-ai/deep-agents-orchestration

INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.

langchain-ai/framework-selection

INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.

langchain-ai/langchain-dependencies

INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.

langchain-ai/langchain-fundamentals

Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.

langchain-ai/langchain-middleware

INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.

langchain-ai/langchain-rag

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

langchain-ai/langgraph-human-in-the-loop

INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.

langchain-ai/langgraph-persistence

INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, thread_id, time travel, Store, and subgraph persistence modes.

langchain-ai/swarm

Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.

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