langgraph-master
PROACTIVE SKILL - Comprehensive guide for building AI agents with LangGraph. Claude invokes this skill automatically when LangGraph development is detected, providing architecture patterns, implementation guidance, and best practices.
Installation
/plugin marketplace add hiroshi75/ccplugins
/plugin install protografico@hiroshi75
Automatic Triggers
Claude automatically invokes this skill when:
- LangGraph development - Detecting LangGraph imports or StateGraph usage
- Agent architecture - Planning or implementing AI agent workflows
- Graph patterns - Working with nodes, edges, or state management
- Keywords detected - When user mentions: LangGraph, StateGraph, agent workflow, node, edge, checkpointer
- Implementation requests - Building chatbots, RAG agents, or autonomous systems
No manual action required - Claude provides LangGraph expertise automatically.
Workflow
Detect LangGraph context → Auto-invoke skill → Provide patterns/guidance → Implement with best practices
Manual Invocation (Optional)
To manually trigger LangGraph guidance:
/protografico:langgraph-master
For learning specific patterns:
/protografico:langgraph-master "explain routing pattern"
Learning Resources
The skill provides comprehensive documentation covering:
| Category | Topics | Files |
|---|---|---|
| Core Concepts | State, Node, Edge fundamentals | 01core_concepts*.md |
| Architecture | 6 major graph patterns (Routing, Agent, etc.) | 02graph_architecture*.md |
| Memory | Checkpointer, Store, Persistence | 03memory_management*.md |
| Tools | Tool definition, Command API, Tool Node | 04tool_integration*.md |
| Advanced | Human-in-the-Loop, Streaming, Map-Reduce | 05advanced_features*.md |
| Models | Gemini, Claude, OpenAI model IDs | 06_llm_model_ids*.md |
| Examples | Chatbot, RAG agent implementations | example_*.md |
Subagent: langgraph-engineer
The skill includes a specialized protografico:langgraph-engineer subagent for efficient parallel development:
Key Features
- Functional Module Scope: Implements complete features (2-5 nodes) as cohesive units
- Parallel Execution: Multiple subagents can develop different modules simultaneously
- Production-Ready: No TODOs or placeholders, fully functional code only
- Skill-Driven: Always references langgraph-master documentation before implementation
When to Use
- Feature Module Implementation: RAG search, intent analysis, approval workflows
- Subgraph Patterns: Complete functional units with nodes, edges, and state
- Tool Integration: Full tool integration modules with error handling
Parallel Development Pattern
Planner → Decompose into functional modules
├─ langgraph-engineer 1: Intent analysis module (parallel)
│ └─ analyze + classify + route nodes
└─ langgraph-engineer 2: RAG search module (parallel)
└─ retrieve + rerank + generate nodes
Orchestrator → Integrate modules into complete graph
How It Works
- Context Detection - Claude monitors LangGraph-related activities
- Trigger Evaluation - Checks if auto-invoke conditions are met
- Skill Invocation - Automatically invokes langgraph-master skill
- Pattern Guidance - Provides architecture patterns and best practices
- Implementation Support - Assists with code generation using documented patterns
Example Use Cases
Automatic Guidance
# Claude detects LangGraph usage and automatically provides guidance
from langgraph.graph import StateGraph
# Skill auto-invoked → Provides state management patterns
class AgentState(TypedDict):
messages: list[str]
Pattern Implementation
User: "Build a RAG agent with LangGraph"
Claude: [Auto-invokes skill]
→ Provides RAG architecture pattern
→ Suggests node structure (retrieve → rerank → generate)
→ Implements with checkpointer for state persistence
Subagent Delegation
User: "Create a chatbot with intent classification and RAG search"
Claude: → Decomposes into 2 modules
→ Spawns langgraph-engineer for each module (parallel)
→ Integrates completed modules into final graph
Benefits
- Faster Development: Pre-validated architecture patterns reduce trial and error
- Best Practices: Automatically applies LangGraph best practices and conventions
- Parallel Implementation: Efficient development through subagent delegation
- Complete Documentation: 40+ documentation files covering all aspects
- Production-Ready: Guidance ensures robust, maintainable implementations