Chinese AI Text Humanizer & Detector

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Detects and rewrites AI-generated Chinese text to increase naturalness and reduce AIGC detection scores across academic and social platforms.

This skill provides a comprehensive toolchain for analyzing and transforming AI-generated Chinese content into human-like text. It leverages a sophisticated multi-paragraph rewriting engine, scene-aware logistic regression fusion, and style-specific transforms for platforms like Zhihu, Xiaohongshu, and academic journals. By combining 20+ rule categories with statistical features like sentence-length variation and perplexity, it significantly reduces AIGC signatures for databases such as CNKI and Wanfang. The tool operates as a pure Python, offline-first solution, ensuring privacy while offering 'best-of-N' optimization to achieve the most natural linguistic results.

Key Features

01Scene-aware AI detection with 95% accuracy using statistical features and LR fusion.
02Best-of-N rewriting logic that automatically selects the version with the lowest AI signature.
03Specialized academic reduction mode for CNKI, VIP, and Wanfang AIGC detection.
04Dependency-free Python implementation for fast, private, and offline text processing.
05Eight distinct style transforms including Xiaohongshu, Zhihu, and literary prose.
061,851 GitHub stars

Use Cases

01Removing structural 'AI flavor' from long-form technical reports or creative novels.
02Lowering AIGC detection percentages in academic papers and theses.
03Polishing AI-generated drafts into natural, social-media-ready posts for WeChat or Weibo.