Detect and rewrite AI writing patterns to produce natural prose.
npx skills add https://github.com/GPTtang/skill-atlas --skill ai-humanizer
Please help me install this Agent Skill. Skill: ai-humanizer Source: https://github.com/GPTtang/skill-atlas/tree/main/skills/writing/ai-humanizer Command: npx skills add https://github.com/GPTtang/skill-atlas --skill ai-humanizer
This Skill transforms sterile, AI-generated text into natural, human-sounding prose by identifying and eliminating common AI writing patterns and statistical anomalies.
Use the ai-humanizer skill to rewrite the following text to sound more human: [Paste your AI-generated text here].
High-intent search queries and answers about installing and using this skill.
To make AI-generated text sound more human, you can rewrite it by detecting common LLM output patterns and statistical anomalies. This process targets content, language, and style to produce natural, specific, and human-like prose.
AI text typically exhibits 24 distinct writing patterns across content, language, and style, alongside statistical anomalies in burstiness, type-token ratio, and sentence length variation. Identifying these helps effectively humanize the output.
To rewrite robotic LLM output, apply humanization rewrites to problematic sections identified through vocabulary and statistical analysis. This refines the draft to sound natural, specific, and engaging with genuine personality.
Yes, you can use LangChain and OpenAI integrations to analyze and detect AI writing patterns. The system evaluates statistical anomalies and a catalog of 500+ AI vocabulary terms to identify and rewrite generic text.
The best way to remove AI vocabulary is to scan the text against a catalog of 500+ common AI terms and 24 writing patterns. Rewriting these flagged elements ensures the content sounds like a human wrote it.
Low burstiness and uniform sentence length are statistical anomalies common in AI writing. Humanizing the text involves evaluating these metrics and rewriting sections to introduce natural sentence length variation and specific language.
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