Total 44,080 skills, Code Quality has 2066 skills
Showing 12 of 2066 skills
Review an existing game codebase for architecture, performance, and best practices
Local code review tool for self-inspection before git push. Triggered when users request phrases like "review my code", "check code changes", "review this commit", "review this", "code review", "git review", "help me check my code". Supports reviewing unstaged, staged uncommitted, and committed unpushed changes, and outputs a Markdown review report with scores.
Comprehensive TypeScript file audit system. Command-only skill (no natural triggers). Accepts file or directory path to systematically audit through accelint-ts-testing, accelint-ts-best-practices, accelint-ts-performance, and accelint-ts-documentation skills. Maintains progress tracking across sessions with interactive change approval. Uses isolated git worktrees to enable parallel audits without conflicts.
Enforces JSDoc documentation standards for this TypeScript project. This skill should be used when writing or reviewing TypeScript code to ensure proper documentation with file preambles, function docs, interface docs, and the critical distinction between documenting "what" vs "why". Use this skill to understand the project's JSDoc ESLint rules and established patterns.
Runs Sweepi and resolves lint violations using Sweepit rule docs. Trigger when asked to run Sweepi, when linting (or asked to lint), and before proposing commits.
Worker that checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates architectural decisions via MCP Ref: (1) Optimality (2) Compliance (3) Performance. Reports issues with SEC-, PERF-, MNT-, ARCH-, BP-, OPT- prefixes.
L3 Worker. Goal-based open-source replacement auditor: discovers custom modules (>100 LOC), analyzes PURPOSE via code reading, searches OSS alternatives via MCP Research (WebSearch, Context7, Ref), evaluates quality (stars, maintenance, license, CVE, API compatibility), generates migration plan.
Multi-language SOLID detection rules. Project type detection, interface locations, file size limits per language.
Comprehensive GitHub code review with AI-powered swarm coordination
Performs semantic code intelligence and token optimization through context engineering and automated context packing. Use when reducing token overhead for large codebases, creating repository digests with Gitingest, packaging code context with Repomix, or tracing cross-file dependencies with llm-tldr.
Review current uncommitted git changes with full file context and produce a structured report with severity levels, actionable fixes, and an approval verdict.
Review code for bugs, security vulnerabilities, performance issues, accessibility gaps, and CLAUDE.md workflow compliance. Supports any tech stack - HTML/CSS/JS, React, TypeScript, Node.js, Python, NestJS, Next.js, and more. Use when completing features, before commits, or reviewing pull requests.