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Found 76 Skills
Code quality gatekeeper and auditor. Enforces strict quality gates, resolves the AI verification gap, and evaluates codebases across 12 critical dimensions with evidence-based scoring. Use when auditing code quality, reviewing AI-generated code, scoring codebases against industry standards, or enforcing pre-commit quality gates. Use for quality audit, code review, codebase evaluation, security assessment, technical debt analysis.
Systematic detection and prioritization of neglected code quality issues: stale TODOs, unused imports, deprecated functions, high complexity, dead code. Use when user requests "code cleanup", "find TODOs", "technical debt scan", or "quality of life fixes". Do NOT use for bug fixing (use systematic-debugging), feature work (use test-driven-development), or formatting-only (use code-linting).
Reviews codebases, architectures, PRs, and technical plans for vanity engineering — code and systems built for the developer's ego, resume, or intellectual pleasure rather than delivering user or business value. Triggers on: "review this code", "is this over-engineered", "code review", "architecture review", "complexity audit", "vanity check", "is this necessary", "simplify this", "tech debt review", or any request to evaluate whether code or architecture is justified by actual requirements. Also trigger when the user shares a codebase and asks for feedback, when discussing framework/library choices, when reviewing PRs, or when someone is debating whether to refactor or rebuild. Nudge activation when you detect patterns of unnecessary abstraction, premature optimization, or resume-driven technology choices in code the user shares — even if they haven't asked for a vanity review.
Comprehensive code review with parallel specialist sub-agents. Analyzes requirements traceability, code quality, security, performance, accessibility, test coverage, and technical debt. Produces detailed findings and calls /qa-gate for final gate decision.
Apply systematic code refactoring with small steps, clear boundaries, and proven techniques. Use when improving existing code, reducing technical debt, cleaning up legacy code, or when user mentions refactoring, code cleanup, or code improvement.
Systematic code refactoring following Martin Fowler's catalog. Methodologies: characterization tests, Red-Green-Refactor, incremental transformation. Capabilities: SOLID compliance, DRY cleanup, code smell detection, complexity reduction, legacy modernization, design patterns, functional programming patterns. Actions: refactor, extract, inline, rename, move, simplify code. Keywords: refactor, SOLID, DRY, code smell, complexity, extract method, inline, rename, move, clean code, technical debt, legacy code, design pattern, characterization test, Red-Green-Refactor, functional programming, higher-order function, immutability, pure function, composition, currying, side effects. Use when: improving code quality, reducing technical debt, applying SOLID principles, fixing DRY violations, removing code smells, modernizing legacy code, applying design patterns.
Analyzes code comments for accuracy, completeness, and long-term maintainability. Identifies misleading comments, comment rot, and documentation gaps. Triggers: After adding documentation, before finalizing a PR, when reviewing comments. Examples: - "Check if the comments are accurate" -> verifies comments match code behavior - "Review the documentation I added" -> analyzes new comments for quality - "Analyze comments for technical debt" -> finds outdated or misleading comments - "Are my docstrings correct?" -> validates documentation accuracy
Explores codebase to find patterns, similar features, and constraints
Scans codebases for technical debt with AST parsing, prioritizes debt items by impact, and generates trend dashboards. Use when tracking tech debt, prioritizing refactoring, or measuring code quality trends over time.
This skill should be used when the user asks to "audit this codebase", "audit this code", "security audit", "code audit", "find vulnerabilities", "check for bugs", "review code quality", "find dead code", "check for anti-patterns", "performance audit", "check for code smells", "technical debt", or "code health check".
Aggressively clean up a codebase by removing AI slop, dead code, weak types, defensive over-engineering, duplication, and legacy cruft. Orchestrates 8 specialized subagents in parallel to deduplicate code, consolidate types, kill unused code, untangle circular dependencies, strengthen weak types, remove unnecessary try/catch, delete deprecated/legacy paths, and strip unhelpful comments. Use when the user asks to 'clean up the codebase', 'remove slop', 'improve code quality', 'remove dead code', 'kill AI slop', 'tighten types', 'remove legacy code', 'deduplicate code', 'DRY this up', 'untangle dependencies', or wants a thorough code quality pass. Also use when the user mentions code smells, technical debt cleanup, or refactoring for clarity — even if they don't use the word 'slop'.
Find technical debt patterns in codebases. Use when asked to find duplicated code, inconsistent patterns, or refactoring opportunities.