What patterns does this skill detect?

It identifies common AI tropes like corporate buzzwords (e.g., 'seamlessly integrates'), formulaic transitions, academic passive voice, and repetitive sentence structures.

Can I use this for existing content?

Yes, the skill can be triggered to review and edit existing documents to improve their authenticity and readability when you mention quality or detection.

How does this improve my documentation?

It replaces vague, robotic language with specific technical descriptions, trade-offs, and varied structures that make the content feel more authoritative and human.

Does it provide a way to measure improvement?

Yes, it includes an automated script that produces an authenticity score (0-100) based on pattern frequency and the presence of authentic markers.

AI Pattern Detection

Name: AI Pattern Detection
Author: jmagly

byjmagly

•

Content Management

Identifies robotic AI-writing patterns and suggests authentic, human-like alternatives to improve content quality and readability.

About

The AI Pattern Detection skill is a specialized tool for Claude Code designed to eliminate the 'AI smell' from generated text. It automatically scans documentation, marketing copy, and technical prose for corporate buzzwords, formulaic transitions, and repetitive structural patterns. By providing specific, context-aware replacement suggestions, this skill helps users maintain a natural, professional voice that emphasizes domain-specific knowledge and real-world constraints over generic LLM tropes. It is an essential component for teams using autonomous agents who want their output to remain indistinguishable from high-quality human writing.

Key Features

Detects structural monotony such as overused three-item lists and em-dashes
Provides context-aware replacement guidelines for technical and creative writing
Identifies and corrects formulaic transitions like 'Moreover' and 'In conclusion'
Scans for critical AI-signature buzzwords and vague intensifiers
Generates authenticity scores based on domain-specific vocabulary and variety
67 GitHub stars

Use Cases

Refining technical documentation to remove repetitive and robotic phrasing
Reviewing PR descriptions and developer communications for a natural professional tone
Polishing marketing copy to ensure it sounds authentic and persuasive

About

Key Features

Detects structural monotony such as overused three-item lists and em-dashes
Provides context-aware replacement guidelines for technical and creative writing
Identifies and corrects formulaic transitions like 'Moreover' and 'In conclusion'
Scans for critical AI-signature buzzwords and vague intensifiers
Generates authenticity scores based on domain-specific vocabulary and variety
67 GitHub stars

Use Cases

Refining technical documentation to remove repetitive and robotic phrasing
Reviewing PR descriptions and developer communications for a natural professional tone
Polishing marketing copy to ensure it sounds authentic and persuasive