SpillwaveSolutions

Mastering Langgraph Agent Skill — AI skill for Claude Code

AI community

Build stateful AI agents and agentic workflows with LangGraph in Python.

How to install Mastering Langgraph Agent Skill

This entry records only its repository, not the path inside it, so there is no exact command to give. Open SpillwaveSolutions/mastering-langgraph-agent-skill and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Mastering Langgraph Agent Skill does

Build stateful AI agents and agentic workflows with LangGraph in Python. Covers tool-using agents, branching workflows, memory persistence, human-in-the-loop, multi-agent systems, and production deployment. Supports 14+ AI coding agents via Agent Skill Standard.

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README

Mastering LangGraph Agent Skill

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/) [![LangGraph](https://img.shields.io/badge/LangGraph-latest-green.svg)](https://github.com/langchain-ai/langgraph) [![Agent Skill Standard](https://img.shields.io/badge/Agent%20Skill-Standard-purple.svg)](https://agentskills.io/) [![SkillzWave](https://img.shields.io/badge/SkillzWave-Marketplace-orange.svg)](https://skillzwave.ai/skill/SpillwaveSolutions__mastering-langgraph-agent-skill__mastering-langgraph__SKILL/)

Build stateful AI agents and agentic workflows with LangGraph in Python. This skill provides comprehensive guidance for tool-using agents, branching workflows, conversation memory, human-in-the-loop oversight, multi-agent systems, and production deployment.

Overview
Key Concepts
Quick Start
Reference Documentation
Requirements
Installation
License

Overview

This skill covers essential LangGraph patterns for building production-ready AI agents:

Topic	Description
Tool-Using Agents	LLM-tool loops that continue until task completion
Branching Workflows	Multi-step pipelines with conditional routing
Persistence & Memory	Checkpointers for conversation context across sessions
Human-in-the-Loop	Pause workflows for human approval with `interrupt()`
Multi-Agent Systems	Supervisor and swarm patterns for agent collaboration
Production Deployment	LangGraph Platform, Docker, and self-hosted options
Debugging	Time-travel, LangSmith tracing, and testing strategies