Skill: openlark/turnitin-ai-checker (version 1.0.0)

--- name: turnitin-ai-checker description: Turnitin AI Detection Checker - Check if text would be flagged by Turnitin's AI detection before submitting. --- # Turnitin AI Checker ## Overview This skill helps users check if their text would be flagged by Turnitin's AI detection system before submitting academic work. It provides AI detection scoring, detailed analysis of AI patterns, and text humanization to help content pass detection. ## Use Cases Use when users want to check AI detection scores, analyze text for AI patterns, or humanize content to pass Turnitin detection. Triggers include "Turnitin", "AI checker", "AI detection", "check AI score", "humanize text", "AI detector", "check if AI wrote this", "detect AI content", "is this AI-generated", "GPTZero alternative", "Turnitin alternative", "analyze text for AI patterns". ## What Is Turnitin AI Detection? Turnitin is the world's most widely used academic integrity platform, deployed by over 15,000 institutions across 140+ countries. In 2023, Turnitin added AI writing detection alongside its plagiarism checking suite. Unlike standalone tools like GPTZero, Turnitin is embedded directly into Learning Management Systems such as Canvas, Blackboard, Moodle, and Google Classroom. When you submit an assignment through your school's LMS, Turnitin scans it automatically. ### Turnitin AI Writing Report Scores - **AI-generated text score**: Percentage of text likely written by AI - **AI-paraphrased text score**: Percentage of text that was AI-generated then paraphrased - **Detection threshold**: Turnitin flags submissions at 20% AI or above - **Below 20%**: No highlights shown to instructors Since August 2025, the system also detects text run through bypasser or paraphrasing tools. The February 2026 model update improved detection recall. ## Core Capabilities ### 1. AI Detection Analysis Analyze text to estimate how Turnitin would score it: - **Perplexity analysis**: Measures how predictable the text is (lower perplexity = more AI-like) - **Burstiness detection**: Analyzes sentence length variation (AI tends to be more uniform) - **Readability scoring**: Checks complexity patterns typical of AI text - **AI fingerprint detection**: Identifies common AI writing patterns ### 2. AI Score Reporting Generate a comprehensive report with: - Overall AI probability percentage - Breakdown by paragraph/section - Specific AI patterns detected - Risk assessment (Safe / Warning / High Risk) ### 3. Text Humanization Rewrite AI-detected text to appear more human-written: - **Academic mode**: Preserves scholarly tone, citations, and technical vocabulary - **Natural variation**: Introduces human-like sentence length variation - **Personal touches**: Adds subjective elements and unique phrasing - **Citation preservation**: Maintains all references and academic formatting ## Workflow ### Check Turnitin AI Score 1. **Receive text**: Accept essay, research paper, or any academic text 2. **Analyze**: Run multiple detection methods (perplexity, burstiness, patterns) 3. **Calculate score**: Estimate Turnitin AI percentage 4. **Report results**: Show score and risk level 5. **Offer humanization**: If score > 20%, suggest humanization ### Humanize Text 1. **Analyze flagged sections**: Identify high-AI segments 2. **Apply transformations**: - Vary sentence lengths (add short punchy sentences, occasional long complex ones) - Replace formal AI phrases with natural alternatives - Add personal opinions or subjective language where appropriate - Introduce minor grammatical variations humans make - Break up overly structured paragraphs 3. **Preserve**: Citations, technical terms, academic tone 4. **Verify**: Re-check humanized text to ensure it passes detection ## Detection Methods Used ### Perplexity Analysis - Measures how "surprised" a language model is by the text - AI-generated text typically has lower perplexity (more predictable) - Human writing has higher perplexity (more creative/unpredictable) ### Burstiness Detection - Analyzes variation in sentence length and structure - AI tends to produce consistent sentence patterns - Human writing has natural "bursts" of variation ### AI Pattern Recognition - Detects common AI phrases and structures - Identifies overly formal or generic language - Spots repetitive transitions and conclusions ### Readability Metrics - Flesch Reading Ease score - Flesch-Kincaid Grade Level - Sentence complexity analysis ## Usage Examples **Example 1: Check Essay** ``` User: "Check this essay for Turnitin AI detection" → Analyze text → Report: "AI Score: 35% (High Risk). Flagged sections: introduction and conclusion" → Offer humanization ``` **Example 2: Humanize Content** ``` User: "My paper scored 40% AI, help me fix it" → Identify problematic sections → Humanize while preserving academic tone → Re-check: "New AI Score: 12% (Safe)" ``` **Example 3: Pre-submission Check** ``` User: "I'm about to submit my thesis, check it first" → Full analysis → Report: "AI Score: 8% (Safe). No action needed." ``` ## Important Notes - This tool provides an **estimate** based on similar detection methods, not official Turnitin results - Actual Turnitin scores may vary slightly - Always review humanized text for accuracy and meaning preservation - Academic integrity is the user's responsibility - this tool helps avoid false positives, not bypass legitimate detection ## Resources - `references/detection_methods.md` - Detailed technical documentation on AI detection algorithms


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