Total 54,862 skills, Code Quality has 2463 skills
Showing 12 of 2463 skills
Write TypeScript and JavaScript code like a top engineer using functional programming principles. Use when writing new code, reviewing existing code, or refactoring TS/JS projects. Applies pure functions, immutability, function composition, higher-order functions, declarative style, and avoiding shared state using native patterns only (no external libraries). Always analyzes the existing codebase first to understand patterns and conventions before making changes or suggestions.
Implement Supabase lint rules, policy enforcement, and automated guardrails. Use when setting up code quality rules for Supabase integrations, implementing pre-commit hooks, or configuring CI policy checks for Supabase best practices. Trigger with phrases like "supabase policy", "supabase lint", "supabase guardrails", "supabase best practices check", "supabase eslint".
Rust code style and conventions for Syncpack. Use when writing or modifying Rust code. Covers functional patterns, imports, naming, and quality standards.
Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.
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.
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.