Total 30,680 skills, Code Quality has 1620 skills
Showing 12 of 1620 skills
Type-driven design principle: transform unstructured data into structured types at system boundaries, making illegal states unrepresentable. Use when writing or reviewing code that validates input, designs data types, defines function signatures, handles errors, or models domain logic. Use when you see validation functions that return void/undefined, redundant null checks, stringly-typed data, boolean flags controlling behavior, or functions that can receive data they shouldn't. Triggers on: "parse don't validate", "type-driven design", "make illegal states unrepresentable", "input validation", "data modeling", "refactor types", "strengthen types", "smart constructor", "newtype", "branded type".
Use this skill when orchestrating multiple review types. Use when general review needed without knowing which specific skill applies, full multi-domain review desired, integrated reporting needed. Do not use when specific review type known - use bug-review, test-review, etc. DO NOT use when: architecture-only focus - use architecture-review.
Open interactive code review for current changes using Plannotator UI
Audit rapidly generated or AI-produced code for structural flaws, fragility, and production risks.
Retrieve code review results from DeepSource — issues, vulnerabilities, report cards, and analysis runs. Use when asked about code quality, security findings, dependency CVEs, coverage metrics, or analysis status.
Skill for creating custom lint rules by leveraging the existing linter ecosystems of various programming languages. This is a linter designed for AI Agents rather than humans, and its error messages function as correction instruction prompts for AI. Create custom rules in the `lints/` directory using standard methods for each language, including Rust (dylint), TypeScript/JavaScript (ESLint), Python (pylint), Go (golangci-lint), etc. Use this skill in the following scenarios: (1) When you want AI to enforce project-specific coding rules; (2) When you want to create lint rules that output AI-readable correction instructions when violations occur; (3) When you want to enforce naming conventions, structural patterns, and consistency rules through AI-driven linting. Triggers: "Create a linter rule", "Add a lint rule", "Enforce this pattern", "AI linter", "Custom lint", "Code rules", "Naming rules", "Structural rules", "create a linter rule", "add a lint rule", "enforce this pattern", "AI linter".
Simplifies and refines Python code for clarity, consistency, and maintainability while preserving all functionality. Applies dignified-python standards. Focuses on recently modified code unless instructed otherwise.
Fix production issues and review code with Sentry context. Use when asked to fix Sentry errors, debug issues, triage exceptions, review PR comments from Sentry, or resolve bugs.
Implement tasks from the change, writing actual code following the specs and design. Trigger: When the orchestrator launches you to implement one or more tasks from a change.
Systematic debugging workflow — reproduce, investigate, hypothesize, fix, and prevent. Covers root cause analysis, bug category strategies, evidence-based diagnosis, and post-mortem documentation.
Comprehensive skill for 89 refactoring techniques and code smells with PHP 8.3+ examples. Covers composing methods, moving features, organizing data, simplifying conditionals, simplifying method calls, dealing with generalization, and detecting 22 code smells across bloaters, OO abusers, change preventers, dispensables, and couplers.
Review Dojo code for best practices, common mistakes, security issues, and optimization opportunities. Use when auditing models, systems, tests, or preparing for deployment.