Token-efficient code review using Tree-sitter AST graphs and MCP. Reduces AI assistant token usage by 6.8–49x by computing blast radius of changes instead of reading entire codebases. Uses SQLite graph database for structural analysis.
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Socratic questioning protocol + user communication. MANDATORY for complex requests, new features, or unclear requirements. Includes progress reporting and error handling.
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Code review guidelines covering code quality, security, and best practices.