Individual skill
langchain-langgraph-agents
Build a correct LangGraph 1.0 ReAct agent with create_react_agent — typed tools, error propagation, recursion caps, and stop conditions that actually stop. Use when writing a first tool-calling agent, migrating from AgentExecutor or initialize_agent, or diagnosing an agent that loops on vague prompts. Trigger with "langgraph agent", "create_react_agent", "langgraph tool calling", "AgentExecutor migration", or "agent loop cost".
plugins/saas-packs/langchain-py-pack/skills/langchain-langgraph-agents/SKILL.md
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- saas Declared skill tag
- langchain Declared skill tag
- langgraph Declared skill tag
- python Declared skill tag
- langchain-1.0 Declared skill tag
- agents Declared skill tag
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# LangChain LangGraph Agents (Python)
## Overview
Two failure modes hit every team writing their first LangGraph 1.0 ReAct agent:
**Loop-to-cap on vague prompts (P10).** `create_react_agent` defaults to
`recursion_limit=25`. A prompt like "help me with my account" never converges —
the model calls a retrieval tool, gets irrelevant results, calls another tool,
and repeats until `GraphRecursionError: Recursion limit of 25 reached without
hitting a stop condition` fires. Cost dashboards show the damage *after* the
fact: $5-$15 per runaway loop on Sonnet with a 3-tool agent, assuming no tool
is itself expensive.
**Silent tool errors on legacy `AgentExecutor` (P09).** The legacy executor