AI-Text-Humanizer-App: Transform AI-generated text into formal, human-like, and academic writing with ease, avoids AI detector

by DadaNanjesha · AI Tool · ★ 433

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install AI-Text-Humanizer-App

git clone https://github.com/DadaNanjesha/AI-Text-Humanizer-App.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

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.

ai-humanizernatural-language-processingnltknltk-pythonnltk-tokenizeropen-sourcepython3transformers

Quick Facts

Stars433
Forks116
LanguagePython
CategoryAI Tool
LicenseMIT
Quality Score66/100
Open Issues6
Last Updated2025-11-11
Created2025-02-07
Platformspython
Est. Tokens~14k

About AI-Text-Humanizer-App

✨ AI Text Humanizer App ✨ Transform AI-generated text into formal, human-like, and academic writing with ease, avoids AI detector! 🚀 Note : (Try It ) Building new version of this project here in this repos https://github.com/DadaNanjesha/AI-content-detector-Humanizer 📌 Features ✅ AI-Powered Text Refinement: Converts AI-generated or informal text into a more academic and human-like format.

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How this security grade is produced

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:

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