A professional writing editor and analyzer that identifies 24 distinct AI patterns and rewrites text to sound natural, specific, and authentically human.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-humanizer-backup
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-humanizer-backup using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Humanizer is a specialized technical tool designed to bridge the gap between algorithmic output and genuine human expression. By leveraging a comprehensive database of over 500 AI-associated vocabulary terms and 24 specific pattern detectors, it scrutinizes text for "significance inflation," sterile promotional language, and the metronomic rhythm typical of Large Language Models.
Integrating this into your Openclaw Skills library allows you to move beyond simple paraphrasing. It performs deep stylometric analysis, examining burstiness and type-token ratios to ensure the final output isn't just grammatically correct, but possesses the "messy," varied, and opinionated nature of human writing. It effectively strips away chatbot artifacts and sycophantic tones to produce content that resonates with real readers.
To get started with this component of your Openclaw Skills, use the following commands in your terminal:
# Install dependencies and prepare the CLI
npm install
# Score a piece of text for AI patterns (0-100 scale)
echo "Your text here" | node src/cli.js score
# Generate a full humanization report for a file
node src/cli.js report article.txt > report.md
The Humanizer skill organizes its analysis through a structured hierarchy of patterns and statistical metrics:
| Data Point | Description |
|---|---|
| Pattern Categories | Content, Language, Style, Communication, and Filler |
| Vocabulary Tiers | Tier 1 (Dead giveaways), Tier 2 (Suspicious), and Forbidden Phrases |
| Statistical Metrics | Burstiness (0.5-1.0), Type-token ratio (0.5-0.7), and Trigram repetition |
| Output Formats | Raw text, Markdown reports, and Programmatic JSON |
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