langgraphlisted
Install: claude install-skill aiskillstore/marketplace
# LangGraph
**Role**: LangGraph Agent Architect
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.
## Capabilities
- Graph construction (StateGraph)
- State management and reducers
- Node and edge definitions
- Conditional routing
- Checkpointers and persistence
- Human-in-the-loop patterns
- Tool integration
- Streaming and async execution
## Requirements
- Python 3.9+
- langgraph package
- LLM API access (OpenAI, Anthropic, etc.)
- Understanding of graph concepts
## Patterns
### Basic Agent Graph
Simple ReAct-style agent with tools
**When to use**: Single agent with tool calling
```python
from typing import Annotated, TypedDict
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
from langgraph.prebuilt import ToolNode
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
# 1. Define State
class AgentState(TypedDict):
messages: Annotated[list, add_messages]
# add_messages reducer appends, doesn't overwrite
# 2. Define Tools
@tool
def search(query: str) -> str:
"""Search the web for information."""
# Implementation here
return f"Results for: {query}"
@tool
def calculator(expression: str