Loading...
Loading...
Found 693 Skills
Python code refactoring skills, covering code smell identification, design pattern application, readability improvement, and practical experience. This skill is applicable when users request "refactor code", "refactor", "code optimization", "improve code quality", "code smell review", "apply design patterns", "enhance readability", or submit code review requests. It supports generating structured refactoring documents after refactoring completion ("output refactoring document", "generate refactoring report"). It includes practical patterns extracted from 20+ real refactoring PRs in the vllm-ascend repository.
Provides refactoring recommendations and step-by-step improvement plans. Use when planning refactoring, improving code structure, or reducing technical debt.
Test coverage verification for refactoring. Apply when verifying existing test coverage, identifying gaps, recommending pre-refactoring tests, and defining verification checkpoints.
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'.
Help users manage technical debt strategically. Use when someone is dealing with legacy code, planning refactoring work, deciding between rewrites vs. incremental fixes, trying to get buy-in for tech debt reduction, or balancing new features with maintenance.
Applies general engineering conventions optimized for AI agents. Use when creating or refactoring codebases and you need strict file discipline, clear module boundaries, naming/layout rules, and anti-pattern avoidance.
Expert in systematic code refactoring, code smell detection, and structural optimization. Use PROACTIVELY when encountering duplicated code, long methods, complex conditionals, or any code quality issues. Detects code smells and applies proven refactoring techniques without changing external behavior.
Ruby and Rails best practices following POODR and Refactoring Ruby. Use for Rails development guidance, code quality, dependency injection, small methods, and OOP principles. Triggers on "rails best practice", "poodr", "refactoring", "ruby oop", "code quality".
Systematic refactoring of codebase components through a structured 3-phase process. Use when asked to refactor, restructure, or improve specific components, modules, or areas of code. Produces research documentation, change proposals with code samples, and test plans. Triggers on requests like "refactor the authentication module", "restructure the data layer", "improve the API handlers", or "clean up the payment service".
Principal Architect for repo audits, complexity analysis, and refactoring recommendations.
Applies software engineering best practices, design principles, and avoids common anti-patterns. Use when designing systems, reviewing code quality, refactoring legacy code, making architectural decisions, or improving maintainability.
Provides structural context for downstream review and refactoring workflows. Use when before architecture reviews to understand file organization, exploring unfamiliar codebases to map structure, estimating scope for refactoring or migration. Do not use when general code exploration - use the Explore agent. DO NOT use when: searching for specific patterns - use Grep directly.