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+# 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                | 01*core_concepts*\*.md      |
+| **Architecture**  | 6 major graph patterns (Routing, Agent, etc.) | 02*graph_architecture*\*.md |
+| **Memory**        | Checkpointer, Store, Persistence              | 03*memory_management*\*.md  |
+| **Tools**         | Tool definition, Command API, Tool Node       | 04*tool_integration*\*.md   |
+| **Advanced**      | Human-in-the-Loop, Streaming, Map-Reduce      | 05*advanced_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
+
+1. **Feature Module Implementation**: RAG search, intent analysis, approval workflows
+2. **Subgraph Patterns**: Complete functional units with nodes, edges, and state
+3. **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
+
+1. **Context Detection** - Claude monitors LangGraph-related activities
+2. **Trigger Evaluation** - Checks if auto-invoke conditions are met
+3. **Skill Invocation** - Automatically invokes langgraph-master skill
+4. **Pattern Guidance** - Provides architecture patterns and best practices
+5. **Implementation Support** - Assists with code generation using documented patterns
+
+## Example Use Cases
+
+### Automatic Guidance
+
+```python
+# 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
+
+## Reference Links
+
+- [LangGraph Official Docs](https://docs.langchain.com/oss/python/langgraph/overview)
+- [LangGraph GitHub](https://github.com/langchain-ai/langgraph)