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Found 59 Skills
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 finds outdated or misleading comments - "Are my docstrings correct?"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
Provides refactoring recommendations and step-by-step improvement plans. Use when planning refactoring, improving code structure, or reducing technical debt.
Systematic framework for resurrecting and modernizing legacy codebases through archaeology, resurrection, and rejuvenation phases. Activate on "legacy code", "inherited codebase", "no documentation", "technical debt", "resurrect", "modernize". NOT for greenfield projects or well-documented active codebases.
Invoke IMMEDIATELY via python script when user requests refactoring analysis, technical debt review, or code quality improvement. Do NOT explore first - the script orchestrates exploration.
Apply named refactoring transformations to improve code structure without changing behavior. Use when the user mentions "refactor this", "code smells", "extract method", "replace conditional", or "technical debt". Covers smell-driven refactoring, safe transformation sequences, and testing guards. For code quality foundations, see clean-code. For managing complexity, see software-design-philosophy.
Iterative codebase quality audit with multi-agent validation and escalating-depth SEEK/VALIDATE/FIX/RECURSE cycle. Use for quality audit, code audit, codebase review, technical debt audit, refactoring opportunities, module quality check, or architecture review.
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'.
Expertise in Senior Principal Engineering refactoring. Use when you need to eliminate technical debt, remove "AI Slop," simplify complex logic, and ensure DRY code.
Modernize legacy codebases, migrate frameworks, and reduce technical debt. Use for legacy system updates or framework migrations.
Executes large-scale architectural refactoring and technical debt reduction across the entire codebase. Ensures consistency with modern design patterns.
Analyzes code complexity, technical debt, and industry trends to propose a 3-month strategic roadmap. Aligns engineering effort with business ROI.
Translates engineering metrics (DORA, error rates, technical debt) into business KPIs and financial impact. Helps justify technical investments to stakeholders.