Can I automatically fix the detected issues?

Yes, the skill generates a report with specific suggestions and can be used alongside the scribe:doc-generator skill with a remediation flag to apply fixes.

What exactly is 'AI slop'?

AI slop refers to the repetitive, predictable, and often vapid linguistic patterns frequently found in AI-generated text, such as the overuse of specific buzzwords or overly formal transition phrases.

Is it okay to use some AI-common words occasionally?

Yes. The detector focuses on density and clustering rather than individual word usage, acknowledging that some terms are perfectly valid in specific contexts.

How does the Slop Density Score work?

It calculates a score based on the frequency of Tier 1 (high-confidence) and Tier 2 (medium-confidence) markers relative to the total word count, rating content from 'Clean' to 'Heavy' slop.

Does this skill work on source code?

The skill is optimized for prose, but it effectively scans markdown files, text files, and docstrings within code to ensure technical explanations are concise.

AI Slop Detector

Name: AI Slop Detector
Author: athola

byathola

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130

内容管理

Identifies and remediates AI-generated linguistic markers and patterns in documentation to improve content quality and authenticity.

关于

The AI Slop Detector is a specialized tool for Claude Code designed to audit documentation, technical prose, and blog posts for 'AI slop'—the repetitive vocabulary, predictable structural patterns, and sycophantic phrasing common in LLM-generated text. By analyzing vocabulary density, em dash usage, and sentence length uniformity, it provides a quantitative 'Slop Density Score' and actionable remediation reports. This skill is essential for teams who use AI to draft content but want to ensure their final public-facing documentation maintains a high-quality, human-centric voice.

主要功能

Automated Slop Density Score calculation to categorize content quality
Multi-tier vocabulary scanning for high-confidence AI markers like 'delve' and 'tapestry'
130 GitHub stars
Structural analysis of em dash density, tricolon patterns, and sentence length variance
Detection of sycophantic conversational fillers and empty marketing jargon
Detailed reporting with specific replacement suggestions for identified markers

使用场景

Auditing project READMEs and documentation to remove robotic or repetitive phrasing
Cleaning up draft content generated by LLMs to ensure a professional, human-like tone
Reviewing technical blog posts and tutorials for clarity and impact before publication

关于

主要功能

Automated Slop Density Score calculation to categorize content quality
Multi-tier vocabulary scanning for high-confidence AI markers like 'delve' and 'tapestry'
130 GitHub stars
Structural analysis of em dash density, tricolon patterns, and sentence length variance
Detection of sycophantic conversational fillers and empty marketing jargon
Detailed reporting with specific replacement suggestions for identified markers

使用场景

Auditing project READMEs and documentation to remove robotic or repetitive phrasing
Cleaning up draft content generated by LLMs to ensure a professional, human-like tone
Reviewing technical blog posts and tutorials for clarity and impact before publication