by NulightJens · Claude Skill · ★ 235
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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
| Stars | 235 |
| Forks | 18 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 58.7507043240149/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-24 |
| Created | 2026-07-23 |
| Platforms | claude-code, python |
| Est. Tokens | ~2k |
Looking for a humanizer-stack alternative? If you're comparing humanizer-stack with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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Free, open-source AI writing humanizer and detector. 55 patterns, 5 voices, a 0-100 AI-tell score, and nothing
Make AI output sound human. Strips AI-isms (sycophancy, stock vocab, hedging stacks, em-dash pileups), preserv
Best static AI text humanizer. Two research-grounded LLM-agnostic skills that make AI writing sound human and
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humanizer-stack is 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.. It is categorized as a Claude Skill with 235 GitHub stars.
humanizer-stack is primarily written in Python. It covers topics such as ai-detection, ai-writing, anthropic.
You can find installation instructions and usage details in the humanizer-stack GitHub repository at github.com/NulightJens/humanizer-stack. The project has 235 stars and 18 forks, indicating an active community.
The top alternatives to humanizer-stack on Agent Skills Hub include humanizer-ru, patina, humanizer-skill. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: