Will this skill accidentally delete important technical information?

No, the skill uses a systematic approach with context preservation rules and confidence scoring to ensure technical specifications and architectural rationales remain intact.

Can I customize which patterns are removed?

Yes, the skill supports user customization, allowing you to define personal pattern databases to keep or remove specific phrases based on your project's needs.

What is AI slop in the context of this skill?

AI slop refers to unnecessary conversational filler, excessive politeness, and redundant preambles often generated by LLMs that dilute information density and obscure technical meaning.

Can I preview changes before they are applied?

Yes, the skill supports a preview mode that allows you to review proposed deletions and modifications before any permanent changes are made to your files.

Does it work on source code files?

Yes, it is specifically designed to handle code comment patterns, identifying and removing redundant descriptions that merely repeat the code's existing logic.

AI Text & Code Cleanup

Name: AI Text & Code Cleanup
Author: v1truv1us

byv1truv1us

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콘텐츠 관리

Eliminates AI-generated verbosity, slop, and redundant conversational filler from documentation and code comments.

소개

The text-cleanup skill provides a systematic framework for improving the signal-to-noise ratio in technical content by identifying and removing common AI-generated patterns. It utilizes comprehensive pattern matching and context-aware rules to strip away conversational preambles, hedging language, and redundant explanations while strictly preserving critical technical nuances. This skill is essential for developers and technical writers who want to maintain high-quality, concise documentation and codebases that respect the reader's time and focus on essential information.

주요 기능

Context-aware pruning of redundant code comments and self-evident explanations
2 GitHub stars
Automated removal of AI conversational preambles and excessive politeness
Customizable cleanup modes for documentation, codebases, and general text
Confidence scoring system to ensure technical meaning is preserved
Systematic identification of hedging language and verbose transitions

사용 사례

Refining AI-generated documentation to remove fluff and improve readability
Standardizing team communication by stripping away conversational filler from AI-assisted reports
Cleaning up auto-generated code comments that merely repeat function signatures

소개

주요 기능

Context-aware pruning of redundant code comments and self-evident explanations
2 GitHub stars
Automated removal of AI conversational preambles and excessive politeness
Customizable cleanup modes for documentation, codebases, and general text
Confidence scoring system to ensure technical meaning is preserved
Systematic identification of hedging language and verbose transitions

사용 사례

Refining AI-generated documentation to remove fluff and improve readability
Standardizing team communication by stripping away conversational filler from AI-assisted reports
Cleaning up auto-generated code comments that merely repeat function signatures