langchain-ai/langchain-fundamentals
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langchain-fundamentalsCreate LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and 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.
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 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.
Finalize prompt file using the role of an AI agent to polish the prompt for the end user.
Build Jenkins declarative and scripted pipelines with stages, agents, parameters, and plugins. Implement multi-branch pipelines and deployment automation.
Control Chrome with MCP for fast browser automation, page actions, and extension-based workflows in a small Lite package
Autonomous AI Command Center for Telegram, Discord & Slack. High-precision long-term memory via grep-based RAG and proactive task scheduling. Your self-hosted multi-agent workforce, anywhere.
Go-to-market strategy for AI products. Use when positioning AI products, handling "who is responsible when it breaks" objections, pricing variable-cost AI, choosing between copilot/agent/teammate framing, or selling autonomous tools into enterprises.
Ironbark — A self-improving learning loop for Claude Code. Harvests reusable skills from sessions and shares them across projects.