langgraph
Expert guidance for building stateful, multi-actor AI agents with LangGraph - graphs, nodes, edges, state management, and agent architectures.
npx skills add majiayu000/claude-skill-registry --skill langgraph --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LangGraph Skill Use this skill when building stateful, cyclic AI agent workflows with LangGraph. ## 📚 Documentation Lookup (Context7) Always verify patterns with latest docs: ``` mcp_context7_resolve-library-id(libraryName="langgraph", query="StateGraph conditional edges") mcp_context7_query-docs(libraryId="/langchain-ai/langgraph", query="checkpointer persistence") ``` ## Core Concepts ### 1. State Definition ```python from typing import Annotated, TypedDict from langgraph.graph.message import add_messages class AgentState(TypedDict): messages: Annotated[list, add_messages] context: str iteration: int # With Pydantic from pydantic import BaseModel class State(BaseModel): messages: list = [] current_step: str = "start" ``` ### 2. Basic Graph Structure ```python from langgraph.graph import StateGraph, START, END # Define the graph workflow = StateGraph(AgentState) # Add nodes (functions that transform state) def agent_node(state: AgentState) -> dict: response = llm.invoke(state["messages"]) return {"messages": [response]} def tool_node(state: AgentState) -> dict: # Execute tools based on last message return {"messages": [tool_result]} workflow.add_node("agent", agent_node) workfl
- 📚 Documentation Lookup (Context7)
- Core Concepts
- 1. State Definition
- 2. Basic Graph Structure
- 3. Prebuilt Components
- 4. Checkpointing (Memory/Persistence)
- 5. Human-in-the-Loop
- 6. Subgraphs
- 7. Streaming
- Agent Architectures
- ReAct Agent
- Plan-and-Execute
- Multi-Agent Supervisor
- Best Practices
pip install langgraph pip install langgraph-checkpoint-sqlite # For SQLite persistence
What does the langgraph skill do?
Expert guidance for building stateful, multi-actor AI agents with LangGraph - graphs, nodes, edges, state management, and agent architectures.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill langgraph --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.