building-langgraph-agentslisted

# LangGraph Development Skill ## Quick Reference LangGraph is LangChain's framework for building stateful, multi-actor applications with LLMs. It enables cyclic graphs, conditional branching, persistent state management, and human-in-the-loop workflows. **Key capabilities**: StateGraph for workflow orchestration, checkpointers for persistence, prebuilt ReAct agents, streaming at multiple granularities, and LangGraph Platform for managed deployment. --- ## Table of Contents 1. [When to Use](#when-to-use) 2. [Package Ecosystem](#package-ecosystem) 3. [Quick Start - Python](#quick-start---python) 4. [Quick Start - TypeScript](#quick-start---typescript) 5. [Core Concepts](#core-concepts) 6. [Prebuilt Components](#prebuilt-components) 7. [Common Patterns](#common-patterns) 8. [Quick Persistence Setup](#quick-persistence-setup) 9. [CLI Commands](#cli-commands) 10. [Error Quick Reference](#error-quick-reference) 11. [When to Use REFERENCE.md](#when-to-use-referencemd) 12. [Agent Integration](#agent-integration) 13. [See Also](#see-also) --- ## When to Use This skill is loaded by `backend-developer` when: - `langgraph` in `requirements.txt`, `pyproject.toml`, or `setup.py` - `@langchain/langgraph` in `package.json` dependencies - Python imports: `from langgraph.graph import StateGraph` - Environment variables `LANGSMITH_API_KEY`, `LANGGRAPH_API_URL`, or `LANGCHAIN_API_KEY` present - User mentions "LangGraph", "StateGraph", "agent workflow", "cyclic agent", or "multi-agent gr