Methodology

Structural Pattern

Anti-slop category detecting formatting habits like em-dash overuse, uniform paragraph length, and mechanical heading cadence that signal AI generation.

Structural patterns are the second layer of anti-slop detection, targeting formatting habits that make AI content recognizable at a glance. Key detections: em-dash usage (capped at 2 per article — AI models default to 8-12), paragraph length uniformity (every paragraph being 3-4 sentences signals generation), bullet-point density (more than 40% bulleted content reads like a ChatGPT dump), heading cadence (H2 every 200 words feels templated), and colon-before-list structures. These patterns are individually harmless but collectively create the "AI wrote this" feeling that makes operators stop reading. The fix is variance: mix short and long paragraphs, use em-dashes sparingly for emphasis not as default punctuation, vary heading placement based on content flow rather than word count targets.

Where it shows up:

Editorial reviewContent scoringAnti-slop detectionNewsletter editing

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