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d2f3886ae1
Repository Restructure: - Move all 83 agent .md files to agents/ subdirectory - Add 15 workflow orchestrators from commands repo to workflows/ - Add 42 development tools from commands repo to tools/ - Update README for unified repository structure The commands repository functionality is now fully integrated, providing complete workflow orchestration and development tooling alongside agents. Directory Structure: - agents/ - 83 specialized AI agents - workflows/ - 15 multi-agent orchestration commands - tools/ - 42 focused development utilities No breaking changes to agent functionality - all agents remain accessible with same names and behavior. Adds workflow and tool commands for enhanced multi-agent coordination capabilities.
1.4 KiB
1.4 KiB
model
| model |
|---|
| claude-sonnet-4-0 |
LangChain/LangGraph Agent Scaffold
Create a production-ready LangChain/LangGraph agent for: $ARGUMENTS
Implement a complete agent system including:
-
Agent Architecture:
- LangGraph state machine
- Tool selection logic
- Memory management
- Context window optimization
- Multi-agent coordination
-
Tool Implementation:
- Custom tool creation
- Tool validation
- Error handling in tools
- Tool composition
- Async tool execution
-
Memory Systems:
- Short-term memory
- Long-term storage (vector DB)
- Conversation summarization
- Entity tracking
- Memory retrieval strategies
-
Prompt Engineering:
- System prompts
- Few-shot examples
- Chain-of-thought reasoning
- Output formatting
- Prompt templates
-
RAG Integration:
- Document loading pipeline
- Chunking strategies
- Embedding generation
- Vector store setup
- Retrieval optimization
-
Production Features:
- Streaming responses
- Token counting
- Cost tracking
- Rate limiting
- Fallback strategies
-
Observability:
- LangSmith integration
- Custom callbacks
- Performance metrics
- Decision tracking
- Debug mode
Include error handling, testing strategies, and deployment considerations. Use the latest LangChain/LangGraph best practices.