Discover bugs through a 3-agent adversarial pipeline (finder → adversarial → referee) that exploits sycophancy for high-fidelity results. Use when reviewing code for bugs, especially when single-agent review isn't sufficient.
Design and implement REST APIs with proper routing, validation, error handling, and documentation. Use when: building backend services, microservices, or adding API endpoints to existing applications.
Implement authentication and authorization from scratch. Covers signup, login, sessions, JWT, role-based access, and protected routes. Use when: adding auth to a new or existing app.
Autonomously optimize any Claude Code skill by running it repeatedly, scoring outputs against binary evals, mutating the prompt, and keeping improvements. Based on Karpathy's autoresearch methodology. Use when: optimize this skill, improve this skill, run autoresearch on, make this skill better, self-improve skill, benchmark skill, eval my skill, run evals on. Outputs: an improved SKILL.md, a results log, and a changelog of every mutation tried.
Systematic approach to finding and fixing bugs in any codebase. Use when: debugging errors, investigating unexpected behavior, fixing failing tests, or resolving production issues.
Automated code review for security, quality, and performance. Catches bugs, vulnerabilities, and anti-patterns before they ship. Use when: reviewing PRs, auditing code before release, or checking your own work.
Review uncommitted git changes for bugs/regressions via Codex MCP and present a structured report. Use when asked to review local changes or find bugs in current work. Requires Codex MCP to be configured.
Design database schemas, write migrations, and model relationships. Use when: starting a new project that needs a database, adding tables, designing relationships, or optimizing queries.