{"repo":"NulightJens/humanizer-stack","free":true,"listed":false,"github":"https://github.com/NulightJens/humanizer-stack","clone":"git clone https://github.com/NulightJens/humanizer-stack.git","description":"Two-pass pipeline for removing AI writing tells from outward-facing text: a surface pass plus a structural pass grounded in the StoryScope study. Packaged as Claude Code Skills. Free community: skool.com/jens-ai-community-1306","language":"Python","stars":221,"topics":["ai-detection","ai-writing","anthropic","claude-code","claude-skills","humanizer","writing-tools"],"license":null,"category":"mcp-servers","readme_excerpt":"humanizer-stack A two-pass pipeline for removing the signs of AI writing from outward-facing text, packaged as Claude Code Skills. Most humanizers only fix words. That is the easy half, and it is the half that is decaying fastest. This repo pairs a surface pass with a structural pass, because the research says structure is where the durable fingerprint lives. Free community. I build tools like this in the open inside the Jens AI Community, a free Skool group for putting AI to work in your business. If this repo is useful to you, come join us: https://www.skool.com/jens-ai-community-1306 Why two passes The StoryScope study (Russell et al., 2026) classified 61,608 stories from humans and five LLMs using only discourse-level features, with every style feature withheld. It detected AI text at 93.2% F1 . Then the authors ran AI text through LAMP, a professional span-level rewriting system that strips cliche, purple prose, and redundant exposition. Functionally, a very good surface humanizer. Detection dropped 1.6 points . Meanwhile the surface layer is eroding on its own. GPT 5.4 already cut its em-dash usage sharply, and fine-tuning drops stylistic detection from 97% to 3%. Word-level tells are a moving target. Structural tells require structural rewrites. So: pass 1 fixes the words. Pass 2 fixes the shape. Run them in that order. What is in here Pass 1: humanizer Vocabulary, punctuation, and phrasing. Inflated symbolism, promotional language, superficial \"-ing\" analyses, vague a","default_branch":null,"files":null,"tree":[],"storefront":"/r/NulightJens","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/NulightJens/humanizer-stack/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}