用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/Dokhacgiakhoa/Agent-Skills-4-Vibe-Coding-Website --skill langgraph-engineering命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | langgraph-engineering |
| description | Building stateful, resilient AI agents with LangGraph v1.0. |
| category | orchestration |
| version | 4.0.5 |
| layer | master-skill |
Goal: Build complex, multi-step AI workflows that are reliable, debuggable, and capable of long-running operations.
agent (LLM decides) <-> tools (Execute action).planner (Generate list) -> executor (Loop through list) -> re-planner (Update list).interrupt_before=["tool_node"] to pause execution.MemorySaver (for dev) or PostgresSaver (prod) to persist thread state.thread_id to graph.invoke to maintain conversation history..stream() events to show immediate progress (tokens, node switching) to UI.from langgraph.graph import StateGraph, END
from typing import TypedDict
class AgentState(TypedDict):
messages: list[str]
context: dict
def call_model(state):
# logic...
return {"messages": [response]}
workflow = StateGraph(AgentState)
workflow.add_node("agent", call_model)
workflow.set_entry_point("agent")
workflow.add_edge("agent", END)
app = workflow.compile()
V1.0 Migration Note:
create_react_agent prebuilt is good for simple starts.StateGraph manually.