langgraph-fundamentals 是做什麼的？
撰寫任何 LangGraph 程式碼時，請引用此技能。涵蓋 StateGraph、狀態模式（state schemas）、節點（nodes）、邊（edges）、Command、Send、invoke、串流（streaming）以及錯誤處理（error handling）。
撰寫任何 LangGraph 程式碼時，請引用此技能。涵蓋 StateGraph、狀態模式（state schemas）、節點（nodes）、邊（edges）、Command、Send、invoke、串流（streaming）以及錯誤處理（error handling）。
此技能為 langchain-ai/langgraph-fundamentals，專為開發者在使用 LangGraph 框架建構 AI Agent 工作流程時提供核心指引。它涵蓋了 StateGraph 的建立、狀態模式的定義、節點與邊的配置，以及進階功能如 Command、Send、invoke 和串流處理。無論是使用 Anthropic Claude、Cursor 或 Codex 等平台，此技能都能協助開發者快速上手 LangGraph 的核心概念，並確保程式碼的正確性與效率。透過詳細的錯誤處理指導，它能幫助開發者避免常見的陷阱，並最佳化 Agent 的行為與回應。此技能對於需要建構複雜多步驟任務、狀態管理或動態流程的 AI Agent 專案特別有用。
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langgraph-fundamentalsInstalled? Explore more 程式設計與開發 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
撰寫任何 LangGraph 程式碼時，請引用此技能。涵蓋 StateGraph、狀態模式（state schemas）、節點（nodes）、邊（edges）、Command、Send、invoke、串流（streaming）以及錯誤處理（error handling）。
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 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.
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 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.