threads-humanizer

Solid

Remove the AI tells human readers react to in a Threads post or thread: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity; caps em dashes at one per post, never forces rhythm. Includes --mode audit (500-char fit, hook, one-hashtag cap, link placement, warm tone) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use threads-post-writer). Keywords: humanize, de-AI Threads post, audit before posting.

AI & Automation 33 stars 9 forks Updated 2 days ago MIT

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Quality Score: 82/100

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Skill Content

# Threads Humanizer V3 Rewrites any Threads post or thread to remove the AI tells that human readers notice, and audits a finished draft against the 2026 Threads ranking checklist. Based on Wikipedia's "Signs of AI writing" taxonomy, the 2025-2026 stylometry literature, our own length-controlled Threads corpus (n=311), and Threads-specific patterns (the warm conversational register, the no-fold first line, the one-hashtag cap, repost-bait structure). **V3 (2026-09):** recalibrated on 2026 evidence. Vocabulary is scored by density, em dashes are capped instead of banned, forced rhythm is now a tell instead of a fix, and there is an over-correction guard. **What this skill does not do:** it does not make text "pass" GPTZero, Pangram, Turnitin or Originality. Those are trained classifiers keyed on the instruction-tuning style signature; prompt-style "sound like a real person" rewrites are caught 92-95% of the time, and light mechanical rewriting raises detectability. On post-length text (under 300 words) detector scores are noise. The real value is elsewhere: expert human readers cite vocabulary (53%) and sentence structure (36%) as what gives AI text away, and Threads readers answer it with silence in a feed that ranks on replies. This skill removes what those readers react to. ## What changed in V3 Evidence tier in brackets: [strong] = replicated across 2+ independent 2025-2026 studies or our own length-controlled corpus; [vendor] = single platform or vendor dataset; [weak...

Details

Author
sergebulaev
Repository
sergebulaev/threads-skills
Created
2 months ago
Last Updated
2 days ago
Language
Python
License
MIT

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