Claude Skill
lynote-ai/humanize-text
使用这款开源工具免费将AI文本人性化。绕过Turnitin、GPTZero及所有主流AI检测器。无需注册，无限在线使用。
概览
仓库信息
安装这个 Skill
git clone https://github.com/lynote-ai/humanize-text.gitRegistry 信息
git clone https://github.com/lynote-ai/humanize-text.gitpip install -r requirements.txt
项目简介
一款免费开源的AI文本人性化工具，可将AI生成内容转化为难以检测、类人化的写作风格。绕过Turnitin、GPTZero等主流AI检测器，无需注册，提供无限免费在线使用。
Free open-source AI text humanizer to convert AI-generated content into undetectable, human-like writing. Bypass Turnitin, GPTZero, and all major AI detectors. No sign-up required. Try our unlimited free online tool
要点
- 免费开源，无需注册即可使用
- 绕过Turnitin、GPTZero等主流AI检测器
- 将AI文本转化为类人化、难以检测的写作风格
- 无限免费在线工具使用
- 支持与Dify、n8n、OpenClaw集成
使用场景
- 学生提交论文时避免AI检测
- 内容创作者将AI生成文章人性化
- 研究人员确保AI辅助论文的自然语调
- 营销人员优化AI文案以提高互动
- 开发者通过n8n或Dify将人性化集成到工作流中
README 摘要
## Free Humanize Text: Open-source toolkit to rewrite AI-generated content into natural <p align="center"> <img src="presentation/banner.png" alt="Humanize-Text" width="600"/> </p> <p align="center"> <a href="https://github.com/lynote-ai/humanize-text/stargazers"><img src="https://img.shields.io/github/stars/lynote-ai/humanize-text?style=social" alt="Stars"></a> <a href="https://github.com/lynote-ai/humanize-text/network/members"><img src="https://img.shields.io/github/forks/lynote-ai/humanize-text?style=social" alt="Forks"></a> <a href="https://github.com/lynote-ai/humanize-text/blob/main/LICENSE"><img src="https://img.shields.io/github/license/lynote-ai/humanize-text" alt="License"></a> <a href="https://www.python.org/"><img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="Python"></a> <a href="https://lynote.ai"><img src="https://img.shields.io/badge/Try-Lynote.ai-brightgreen?style=for-the-badge" alt="Lynote.ai"></a> </p> <p align="center"> English | <a href="README-zh.md">中文</a> </p> --- ## What is Humanize-Text? An AI text humanization toolkit. This repo evolved through two stages: - **v1.0** — Documented **4 humanization methodologies** as reference implementations (translation chain, multi-turn LLM rewriting, detection-guided feedback loop, mixed-engine translation). See [docs/techniques.md](docs/techniques.md). - **v1.5 (current)** — Added the **Standard Pipeline**: a production-grade integration of Method 1 (Translation Chain) + Method 2 (LLM Rewriting), fixed as a 5-step chain we actually run and recommend. ### v1.5.1 — Standard Pipeline (Recommended) The Standard Pipeline preserves the original writing style while routing text through a 4-step chain: two DeepSeek humanization rewrites followed by two cross-engine translation