Total 55,492 skills, Code Quality has 2494 skills
Showing 12 of 2494 skills
Comprehensive .NET exception handling quality improvement workflow. Auto-detects .NET projects, investigates 10 common exception handling mistakes, generates prioritized findings, and orchestrates fixes following best practices.
Run /check-quality, then fix the highest priority quality issue. Creates one fix per invocation. Invoke again for next issue. Use /log-quality-issues to create issues without fixing.
Use when fixing Rubocop violations. Runs Rubocop to identify issues, applies fixes following project conventions, and explains non-obvious corrections.
Comprehensive code reviewer for Java and Python implementations focusing on correctness, efficiency, code quality, and algorithmic optimization. Reviews LeetCode solutions, data structures, and algorithm implementations. Use when reviewing code, checking solutions, or providing feedback on implementations.
Code quality validation with linters, SOLID principles, DRY detection, error detection, and architecture compliance across all languages.
Dynamically validate that the implemented codebase matches architectural decisions documented in plan files. Use when validating implementation matches planning documents, checking for architecture drift, or preparing for architecture reviews.
Code refactoring workflow - analyze → plan → implement → review → validate
Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code.
Run a full-scale implementation review with parallel subagents for plan alignment, UI verification, technical and strategic analysis, and test coverage gap closure across app and database layers.
Use when auditing project structure, planning refactors, improving code organization, analyzing dependencies and module boundaries, or identifying structural issues. TypeScript/JavaScript-primary with language-agnostic patterns.
Analyzes code based on John Ousterhout's "A Philosophy of Software Design". Identifies unnecessary complexity, shallow modules, information leaks, and design problems. Use when reviewing architecture, PRs, refactoring, or asking about code quality.
Evaluates and prevents unnecessary abstractions by analyzing interfaces, layers, and patterns against concrete requirements. Use when evaluating new abstractions, reviewing architecture proposals, detecting over-engineering, or simplifying existing code. Triggers on "is this abstraction necessary", "too many layers", "simplify architecture", "reduce complexity", "over-engineered", "do we need this interface", or when reviewing design patterns.