Total 54,997 skills, Code Quality has 2472 skills
Showing 12 of 2472 skills
Check dependencies for vulnerabilities. Use when user asks to "audit dependencies", "/audit-deps", "check for vulnerabilities", or wants to check dependency health.
Automated code review for Arduino/ESP32/RP2040 projects focusing on best practices, memory safety, and common pitfalls. Use when user wants code feedback, says "review my code", needs help improving code quality, or before finalizing a project. Generates actionable checklists and specific improvement suggestions.
Principal Architect for repo audits, complexity analysis, and refactoring recommendations.
Orchestrate parallel debugging agents with root-cause tracing for multi-failure scenarios
Game development expert including DragonRuby, Unity, and game mechanics
Design systems using Martin Fowler's principles of refactoring, continuous integration, and patterns of enterprise application architecture. Emphasizes clean code, evolution over revolution, and writing code for humans first. Use when designing enterprise systems, planning refactors, or establishing engineering culture.
Use when working with fundamental software development knowledge — patterns, algorithms, architecture, and craftsmanship principles drawn from canonical published works. USE FOR: development fundamentals, pattern selection, architecture decisions, algorithm choice, code quality principles, choosing between architectural styles DO NOT USE FOR: specific pattern implementations (use sub-skills: design-patterns, integration-patterns, algorithms, etc.), testing strategy (use testing), infrastructure (use iac)
Pre/post-operation validation to detect missing components and prevent future issues
Audit, compare, and document Opik integrations across Python SDK, TypeScript SDK, and OTEL/API backend. Use when adding a new integration, reviewing an existing one, or generating first-pass integration docs and gap analysis.
Guides technical evaluation of code review feedback before implementation. Use when receiving PR comments, review suggestions, GitHub feedback, or when asked to address reviewer feedback. Emphasizes verification and reasoned pushback over blind agreement.
Hypothesis-driven autonomous debugging with real command validation
Simplify and refine code for clarity, consistency, and maintainability. Use after writing or modifying code to clean it up while preserving all functionality.