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langchain-ai/deep-agents-memory

当您的 Deep Agent 需要内存、持久化或文件系统访问时,请调用此技能。涵盖 StateBackend(临时)、StoreBackend(持久化)、FilesystemMiddleware 以及用于路由的 CompositeBackend。

deep-agents-memory 是什么?

该技能专为 Deep Agent 设计,用于处理记忆存储、状态持久化和文件系统交互。它提供了四种核心后端:StateBackend 用于临时会话数据、StoreBackend 用于跨会话持久化键值存储、FilesystemMiddleware 用于直接的文件读写操作,以及 CompositeBackend 用于将请求智能路由到混合后端。平台支持方面,该技能适用于所有基于 LangChain 的代理框架,包括 Claude Code、Cursor 等。通过调用该技能,代理能够在长时间运行的任务中维持上下文,安全地访问本地文件系统,并根据需求选择临时或永久存储。其模块化架构允许开发者组合不同后端,以优化性能和数据生命周期管理。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/deep-agents-memory

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deep-agents-memory 是做什么的?

当您的 Deep Agent 需要内存、持久化或文件系统访问时,请调用此技能。涵盖 StateBackend(临时)、StoreBackend(持久化)、FilesystemMiddleware 以及用于路由的 CompositeBackend。

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-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-fundamentals

INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.

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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