text-metrics
CommunityDetect AI writing with probabilistic metrics.
System Documentation
What problem does it solve?
Provides automated, probability-based analysis to help detect AI-generated text by delivering GLTR-style token rank histograms, DetectGPT curvature measurements, and Coh-Metrix-inspired cohesion metrics. The skill is designed to compose with the ai-check skill to enable Dimension 5 probability-based detection across documents, transcripts, and code comments. It exposes a simple Python API and ready-to-run instructions.
Core Features & Use Cases
- GLTR-style token rank histograms to quantify token concentration
- DetectGPT curvature probes to assess probability curvature and generation likelihood
- Coh-Metrix-inspired cohesion metrics (connectives, lexical diversity, referential cohesion)
- Easy integration with ai-check for end-to-end probability-based detection scenarios
- Suitable for research, auditing, and automated content verification across text types
Quick Start
Install dependencies from scripts/requirements.txt, load the model(s), and run full_analysis on your input text to produce token ranks, curvature, and cohesion metrics.
Dependency Matrix
Required Modules
Components
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: text-metrics Download link: https://github.com/astoreyai/claude-skills/archive/main.zip#text-metrics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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