Turnitin AI Checker

v1.0.0

Turnitin AI Detection Checker - Check if text would be flagged by Turnitin's AI detection before submitting.

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Prompt PreviewInstall & Setup
Install the skill "Turnitin AI Checker" (openlark/turnitin-ai-checker) from ClawHub.
Skill page: https://clawhub.ai/openlark/turnitin-ai-checker
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

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openclaw skills install turnitin-ai-checker

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npx clawhub@latest install turnitin-ai-checker
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Purpose & Capability
Name/description match the included files and algorithms: detection heuristics (perplexity proxy, burstiness, pattern matching, readability) and text humanization are implemented in the bundled scripts. The skill does not require Turnitin credentials because it only produces an estimate, which is coherent with the description.
Instruction Scope
SKILL.md directs the agent to accept text, analyze it with the provided methods, report scores, and optionally humanize flagged sections. The instructions and code only reference local text-processing functions; they do not instruct reading unrelated files, environment variables, or sending data to external endpoints.
Install Mechanism
No install spec (instruction-only) and included Python scripts are static. No downloads, external package installs, or archive extraction were specified. Risk from install mechanism is low.
Credentials
The skill declares no required environment variables, binaries, or credentials and the code reviewed does not access hidden config or secrets. Requested environment access is proportional to its functionality.
Persistence & Privilege
The skill does not request always:true, does not modify other skills or system configuration, and contains no instructions to persist credentials or change agent-wide settings.
Assessment
This skill appears internally consistent: it implements local heuristics to estimate Turnitin-style AI scores and offers humanization transformations. Important things to consider before installing or using it: (1) Ethical/legal: using humanization to evade plagiarism/AI-detection policies can violate academic integrity rules — don't use it to cheat. (2) Accuracy: the tool provides an estimate, not official Turnitin results; rely on it only as a rough guide and review humanized text carefully for meaning and correctness. (3) Privacy: the skill processes whatever text you submit; avoid pasting sensitive or confidential material unless you trust the execution environment. (4) Non-determinism: humanization uses randomness and may produce variable outputs; re-run and review results. If you want extra assurance, inspect the full scripts in your environment, run them in a sandboxed interpreter, and confirm there are no network calls or additional files beyond those reviewed.

Like a lobster shell, security has layers — review code before you run it.

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86downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

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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