What problem does it solve? Teams building AI agent systems often bolt instructions onto whichever file is open, producing monolithic agents, duplicated instructions, circular dependencies, and bloated context. This Skill routes every new requirement to the correct architectural layer — agent, skill, workflow, context, or platform adapter — keeping the agentic system coherent and maintainable. ## Core Features & Use Cases - Architecture routing: Classifies each new requirement as an agent responsibility, skill capability, workflow lifecycle, project context, or platform adapter change before any file is edited. - Canonical agent model: Defines a baseline Master/Thinker/Planner/Builder/Verifier role system with just-in-time skill loading and compact handoffs to minimize token consumption. - Migration and review: Inventories existing CLAUDE.md/AGENTS.md files, classifies their contents, removes duplication, and produces a platform-neutral architecture with an index.md mapping layer. - Use Case: When a user says "add a new capability to our agent system", the Skill determines whether it belongs in a skill, agent, or workflow, updates only that layer plus index.md, and validates against quality gates for duplication, token efficiency, and portability. ## Quick Start Ask the assistant to review our agent architecture and migrate CLAUDE.md into agents, skills, and workflows.