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bloat-detector

6.6

by athola

103Favorites
83Upvotes
0Downvotes

Detect codebase bloat through progressive analysis: dead code, duplication, complexity, documentation bloat. Triggers: bloat detection, dead code, code cleanup, duplication, technical debt, unused code Use when: context usage high, quarterly maintenance, pre-release cleanup, before refactoring DO NOT use when: active feature development, time-sensitive bugs, codebase < 1000 lines

code-analysis

6.6

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Quick Review

Excellent bloat detection skill with clear progressive tiers, well-structured module architecture, and comprehensive coverage of bloat types. The SKILL.md provides actionable commands, clear when-to-use guidance, and confidence scoring frameworks. Strong structure with modular organization keeps the main file concise while referencing detailed sub-modules. Novelty is solid—detecting AI-generated bloat and git history patterns would be token-intensive for a CLI agent to implement ad-hoc. Minor room for improvement in explicitly stating detection algorithms, but referenced modules likely contain those details.

LLM Signals

Description coverage9
Task knowledge8
Structure9
Novelty7

GitHub Signals

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Last commit 0 days ago

Publisher

athola

athola

Skill Author

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Publisher

athola avatar
athola

Skill Author

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