deodorizing-code

What problem does it solve?

AI-generated code often contains verbose patterns, unnecessary nesting, duplicated logic, hallucinated imports, insecure hard-coded secrets, and missing type information that increase maintenance cost and introduce risks. This Skill helps teams and developers identify these "code smells", prioritize critical problems, and transform generated snippets into concise, idiomatic, and safer code without changing intended behavior.

Core Features & Use Cases

• Detection: Classifies smells such as high cognitive complexity, redundancy, hallucinated dependencies, hard-coded secrets, DRY violations, and zombie code.
• Refactoring patterns: Suggests and documents targeted fixes including guard clauses, method extraction, map lookups, language idiom conversions, and async parallelization for JS/TS.
• Verification & tool guidance: Produces a remediation plan, Before/After metrics, and optional recommendations for static tools (ruff, eslint) and test validation.
• Use cases: Clean up AI-generated PR diffs, harden pasted snippets before production use, and standardize generated helpers across a codebase.

Quick Start

Analyze the changed Python and TypeScript files in my current branch and produce a prioritized refactoring plan that removes code smells, adds necessary type hints, and flags any security risks.