Total 54,475 skills, Code Quality has 2456 skills
Showing 12 of 2456 skills
ShellCheck validation as non-negotiable 2025 workflow practice
User-invoked interface review of a change rather than a screen: uncommitted work, the current branch, or a pull request. Resolves the change scope, expands it to the surfaces it affects, reads both sides of the diff, and classifies every finding as introduced, a regression, or pre-existing, then hands the review to better-interface for domain routing, severity, and the verdict. Covers interface quality, not correctness, tests, or security. Supports quick and full review modes. Triggers on interface-review, review my branch, review my PR, review the diff, review my changes, review before pushing, design regression check, changed files interface review.
Show session analytics, learning patterns, correction trends, heatmaps, and productivity metrics. Use when wanting to understand your coding patterns over time.
Remove AI-style code slop from a branch by reviewing diffs, deleting inconsistent defensive noise, and preserving behavior and local style.
Generate a map of all files relevant to a task before making changes
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Comprehensive toolkit for validating, linting, testing, and automating Ansible playbooks, roles, and collections. Use this skill when working with Ansible files (.yml, .yaml playbooks, roles, inventories), validating automation code, debugging playbook execution, performing dry-run testing with check mode, or working with custom modules and collections.
Core TypeScript conventions for type safety, inference, and clean code. Use when writing TypeScript, reviewing TypeScript code, creating interfaces/types, or when the user asks about TypeScript patterns, conventions, or best practices.
Error handling best practices across languages — error types, recovery strategies, user-facing messages, and logging. Reference when implementing error handling or designing error flows.
Comprehensive performance specialist covering analysis, optimization, load testing, and framework-specific performance. Use when identifying bottlenecks, optimizing code, conducting load tests, analyzing Core Web Vitals, fixing memory leaks, or improving application performance across all layers (application, database, frontend). Includes React-specific optimization patterns.
When writing or reviewing code to prevent over-engineering and speculative features. Use when the user says "is this over-engineered," "do we need this," "should I add," "future-proof," or "just in case." For simplicity concerns, see kiss. For abstraction design, see solid.
Style, review, and refactoring standards for Python codebases with strong typing, explicit error handling, and maintainable module boundaries. Use when Python artifacts are created, changed, or reviewed and Python-specific quality rules must be enforced.