Architects robust, stateless agent evaluation plugins using 12-Factor and MAESTRO principles.
This skill provides specialized architectural guidance for designing Multi-Agent System (MAS) evaluation plugins within Claude Code. It enforces rigorous design patterns such as the Stateless Reducer Pattern, structured Pydantic outputs, and independent context windows to ensure plugins are portable, scalable, and resilient. By following these principles, developers can build evaluation tiers that handle their own errors and state, leading to more reliable AI pipelines and production-grade agentic workflows.
Key Features
01Architecture-level guidance for 12-Factor and MAESTRO compliance
020 GitHub stars
03Structured Pydantic model integration for validated input and output
04Context window management to prevent global state leakage
05Stateless Reducer Pattern implementation for side-effect-free evaluations
06Error handling patterns that favor structured results over exceptions
Use Cases
01Architecting new metrics or evaluation tiers for agentic pipelines
02Refactoring monolithic evaluation engines into modular plugin patterns
03Designing portable evaluation components for production AI systems
