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Found 67 Skills
Refactor codebases using Design by Typed Holes methodology - iterative, test-driven refactoring with formal hole resolution, constraint propagation, and continuous validation. Use when refactoring existing code, optimizing architecture, or consolidating technical debt through systematic hole-driven development.
The practice of restructuring and simplifying code continuously – reducing complexity, improving design, and keeping codebases clean.
Code refactoring expert for improving code quality, readability, maintainability, and performance. Specializes in Java and Python refactoring patterns, eliminating code smells, and applying clean code principles. Use when refactoring code, improving existing implementations, or cleaning up technical debt.
Scan and analyze a software repository or project for design quality using principles from A Philosophy of Software Design by John Ousterhout. Use when user asks to review, audit, scan, or evaluate code quality, design quality, architecture, or technical debt. Also trigger for: code review, design review, complexity analysis, code health check, module depth analysis, information hiding review, how good is my code, review my project, find design problems, what is wrong with my codebase, rate my code, or anything about evaluating software design quality at a structural level. This is not a linter or style checker. It evaluates deep design qualities like module depth, abstraction quality, information hiding, and complexity patterns.
Enforce and guide the Mikado Method when a developer is refactoring, restructuring, or dealing with legacy code. Use this skill whenever the user mentions refactoring, technical debt, legacy code, code restructuring, dependency untangling, or "breaking everything" when making changes. Also trigger when the user wants to make a large change safely, asks how to split a big refactoring task, wants to work on main branch without a long-lived feature branch, or asks how to incrementally improve a codebase. The skill enforces the full Mikado loop: goal → naive attempt → map prerequisites → revert → implement leaves → commit → repeat.
Provides final code cleanup after task review approval. Removes debug logs, temporary comments, dead code, optimizes imports, and improves readability. Use when asked to clean up code, polish, finalize, tidy up, remove technical debt, or prepare code for completion after review. Not for refactoring logic or fixing bugs—focused solely on cosmetic and hygiene cleanup.
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.
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'.