ai-check

# AI-Generated Text Detection Skill

## Purpose

Detect patterns typical of LLM-generated text to ensure natural, human-authored academic writing. This skill helps maintain authenticity in research publications, dissertations, and documentation.

## When to Use This Skill

### Primary Use Cases
1. **Pre-Commit Validation** - Automatically check manuscripts and documentation before git commits
2. **Manuscript Review** - Validate academic writing before submission to journals or committees  
3. **Quality Assurance** - Part of systematic QA workflow for research artifacts
4. **On-Demand Analysis** - Manual review of any text file for AI patterns
5. **Writing Evolution Tracking** - Monitor writing style changes over time

### Specific Scenarios
- Before submitting dissertation chapters to advisor
- Prior to journal article submission
- When reviewing team member contributions
- After making significant edits to documentation
- When suspicious patterns are noticed in writing
- During peer review or committee review preparation

## Detection Methodology

### 1. Grammar Pattern Analysis

**What We Check:**
- **Excessive Perfection**: Zero typos, missing commas, or minor errors throughout
- **Comma Placement**: Perfect comma usage in all complex sentences
- **Formal Register**: Consistent formal tone with no informal elements
- **Grammar Consistency**: No variations in grammatical choices

**Red Flags:**
- Absolutely no grammatical errors in 10+ pages
- Every semicolon and colon used perfectly
- No sentence fragments or run-ons even in appropriate contexts
- Overly formal language even in methods sections

**Human Writing Typically Has:**
- Occasional minor typos or comma splices
- Some inconsistency in formality
- Natural variations in grammar choices
- Context-appropriate informality

### 2. Sentence Structure Uniformity

**What We Check:**
- **Sentence Length Distribution**: Variation in sentence lengths
- **Structural Patterns**: Repetitive sentence structures
- **Compl