HaoNgo232

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.

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.

Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.

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.

Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments

Design thinking and decision-making for web UI. Use when designing components, layouts, color schemes, typography, or creating aesthetic interfaces. Teaches principles, not fixed values.

Game development orchestrator. Routes to platform-specific skills based on project needs.

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.

React and Next.js performance optimization from Vercel Engineering. Use when building React components, optimizing performance, eliminating waterfalls, reducing bundle size, reviewing code for performance issues, or implementing server/client-side…

Apply when analyzing claims, assumptions, user framing, high-stakes decisions, ambiguous evidence, or requests that could lead to overconfident conclusions. Maintain a clear boundary between verified evidence, reported claims, and model inference.