by AIScientists-Dev · Claude Skill · ★ 2.5k
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git clone https://github.com/AIScientists-Dev/academic-humanizer ~/.claude/skills/academic-humanizerTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
One of 23 tools we ran end to end on the same task for our Humanizer & Anti-Slop Skills page (2026-10-07).
Result: Reads human 3.5/5 · Changed wording, not structure · kept every fact · 0.8 min
| Stars | 2,516 |
| Forks | 190 |
| Category | Claude Skill |
| Quality Score | 67/100 |
| Open Issues | 3 |
| Last Updated | 2026-07-03 |
| Created | 2026-06-20 |
| Platforms | claude-code, codex |
| Est. Tokens | ~17k |
Why we built this Some of us write a lot of papers and grant proposals, and our team started using AI to help with drafts. The problem is that AI-assisted drafts come out generic and verbose, with "In recent years..." openers, inflated phrasing, and over-long sentences. They also drift from the author's own voice and lose the precision scholarship depends on.
Looking for a academic-humanizer alternative? If you're comparing academic-humanizer 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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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: