langchain-middleware 是做什么的？
当你需要人工在环审批、自定义中间件或结构化输出时，请使用此技能。涵盖了用于危险工具调用的人工审批中间件、带钩子的自定义中间件、Command 恢复模式以及基于 Pydantic/Zod 的结构化输出。
在需要人工审核、自定义中间件或结构化输出时调用该技能。涵盖用于危险工具调用的人工夹层中间件、带钩子的自定义中间件、Command 恢复模式以及基于 Pydantic/Zod 的结构化输出。
该技能专为 AI 代理（如 Claude Code、Cursor、Codex）设计，提供中间件模式以增强交互安全性和结构化能力。它支持人工在环（HumanInTheLoopMiddleware），用于对危险工具调用进行人工审批；允许开发者通过钩子创建自定义中间件，拦截或修改请求/响应流；并利用 Command 恢复模式实现暂停后继续执行工作流。此外，技能强调结构化输出，通过 Pydantic（Python）或 Zod（TypeScript）定义精确的输出模式，减少解析错误。适用于所有主流 AI 代理平台，尤其适合需要合规、审计或复杂工作流控制的场景。
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langchain-middlewareInstalled? Explore more 编程与开发 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
当你需要人工在环审批、自定义中间件或结构化输出时，请使用此技能。涵盖了用于危险工具调用的人工审批中间件、带钩子的自定义中间件、Command 恢复模式以及基于 Pydantic/Zod 的结构化输出。
This repo contains 11 individual skills — each has its own dedicated page.
INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.
INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.
INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.
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.
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.
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
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.
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.
Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.
Send and manage iMessages via BlueBubbles, including attachments, tapbacks, edits, replies, and groups.
Control Eight Sleep pods (status, temperature, alarms, schedules).
BluOS CLI (blu) for discovery, playback, grouping, and volume.
Create, search, and manage Bear notes via grizzly CLI.
Capture frames or clips from RTSP/ONVIF cameras.
Search GIF providers with CLI/TUI, download results, and extract stills/sheets.