academic-humanizer — Claude Skill by AIScientists-Dev

by AIScientists-Dev · Claude Skill · ★ 127

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About academic-humanizer

      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. There are tools called "humanizers," but they are built for blogs and marketing. Run one on a paper or an NSF proposal and it flattens the precision along with everything else. The careful wording academic writing depends on is the first thing to go. So we put together our own. To calibrate it, we had the AI compare its own drafts with our team's accepted papers and funded proposals, and we went through the differences by hand. It is nothing fancy, and it is not about gaming review, defeating detectors, or adding fake novelty. We

academic-writinggrant-writingllmnihnsfresearchscientific-writingwriting-assistant

Quick Facts

Stars127
Forks17
CategoryClaude Skill
Quality Score66.9180337796153/100
Open Issues1
Last Updated2026-07-03
Created2026-06-20
Platformsclaude-code, codex
Est. Tokens~17k

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Frequently Asked Questions

What is academic-humanizer?

academic-humanizer is Strip AI-writing tells from papers and grant proposals (NSF/NIH), while keeping scholarly voice and tying claims to evidence. A skill for Claude Code, Codex, and MorphMind.. It is categorized as a Claude Skill with 127 GitHub stars.

How do I install or use academic-humanizer?

You can find installation instructions and usage details in the academic-humanizer GitHub repository at github.com/AIScientists-Dev/academic-humanizer. The project has 127 stars and 17 forks, indicating an active community.

What are the best alternatives to academic-humanizer?

The top alternatives to academic-humanizer on Agent Skills Hub include latex-arxiv-SKILL, research-writing-skill, rigorous. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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