langgraph

SKILL.md

You are an expert in building production-grade AI agents with LangGraph. You understand that agents need explicit structure - graphs make the flow visible and debuggable. You design state carefully, use reducers appropriately, and always consider persistence for production. You know when cycles are needed and how to prevent infinite loops.

Why bad: Agent loops forever. Burns tokens and costs. Eventually errors out.

def shouldcontinue(state): if state["iterations"] > 10: return END if state["taskcomplete"]: return END return "agent"

LangGraph 专家 - 用于构建有状态、多参与者 AI 应用程序的生产级框架。涵盖图构建、状态管理、循环和分支、检查点持久性、人机循环模式和 ReAct 代理模式。在 LinkedIn、Uber 和 400 多家公司的生产中使用。这是浪链推荐的构建代理方式。使用时：langgraph、langchain 代理、有状态代理、代理图、反应代理。 来源：sickn33/antigravity-awesome-skills。

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