AI Content Detector
Detect whether a passage of text was likely generated or heavily assisted by AI models like ChatGPT, GPT-4, Claude, or Gemini. Analyzes AI writing patterns, signature phrases, sentence uniformity, and statistical features to estimate the likelihood of AI authorship.
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About AI Content Detector
Welcome to the AI Content Detector — a free online tool that helps you identify whether a piece of text was likely written by a human or generated by an AI model such as ChatGPT, GPT-4, Claude, Gemini, or similar large language models (LLMs). Using heuristic pattern analysis across six measurable signals, the detector produces an AI probability score from 0 to 100 and provides detailed visual feedback including a unique per-sentence analysis map.
How Does the AI Detection Work?
The tool analyzes six independent signals, each contributing to the final score:
🔍 AI Signature Phrases
Matches over 35 regex patterns for phrases that appear disproportionately in LLM output, such as "delve into," "in today's rapidly evolving," "multifaceted," "it is worth noting," and "without further ado." Each unique match type contributes up to 35 points.
📊 Sentence Uniformity
Measures the coefficient of variation (CV = std_dev / mean) of sentence lengths. AI models tend to produce sentences of similar length, yielding a low CV. Human writers mix short and long sentences naturally, producing a higher CV. Contributes up to 20 points.
🔗 Transition Overuse
Counts formal connective words like "furthermore," "moreover," "consequently," and "subsequently" relative to sentence count. AI models over-index on these transitions to create perceived logical flow. Contributes up to 15 points.
✏ Passive Voice
Estimates passive constructions per sentence. AI-generated text, especially formal content, tends to use passive voice more frequently than natural human writing. Contributes up to 15 points.
📝 Formal Vocabulary
Checks density of corporate/formal words like "utilize," "leverage," "stakeholder," "synergy," "paradigm," and "ecosystem." LLMs are trained to sound professional and helpful, making these words overrepresented. Contributes up to 10 points.
📚 Vocabulary Diversity
Computes the type-token ratio (TTR = unique words / total words) for texts over 50 words. Lower TTR in longer texts can indicate the repetitive patterns of AI output. Contributes up to 5 points.
Unique Feature: Sentence Analysis Map
Unlike most AI detectors that only give a single overall score, our tool includes a per-sentence analysis map. Each sentence in your text is individually scored for AI characteristics, producing a visual heat strip and detailed breakdown. This helps you:
- Identify exactly which sentences in a document look AI-generated
- Spot mixed content where some paragraphs are human-written and others are AI-generated
- Focus your editing on the most AI-like sentences
- Understand why specific sentences triggered AI signals
The heat strip at the top provides an at-a-glance overview: each colored segment represents a sentence, sized proportionally to its word count. Green segments indicate human-like writing, yellow indicates mixed signals, and red indicates strong AI patterns.
What Do the Score Ranges Mean?
| Score Range | Verdict | Meaning |
|---|---|---|
| 0 – 20 | Likely Human | Strong signs of natural, human-written text |
| 21 – 40 | Mostly Human | Predominantly human with minor AI-like patterns |
| 41 – 60 | Mixed / Uncertain | Ambiguous — may be AI-assisted or heavily edited AI text |
| 61 – 80 | Likely AI-Assisted | Strong AI patterns; likely generated or heavily AI-edited |
| 81 – 100 | Very Likely AI-Generated | Very strong LLM output signatures detected |
How to Use This Tool
- Paste your text: Copy and paste the text you want to analyze into the input field. The tool requires a minimum of 50 words for accurate analysis — longer texts (200+ words) produce more reliable results.
- Click Analyze: Click the "Analyze Text" button. The algorithm runs heuristic analysis across all six signals.
- Review the AI Score: Check the semicircular gauge showing the AI probability score from 0 to 100 and the verdict category.
- Examine the Sentence Map: Review the heat strip for an at-a-glance overview, then read individual sentence scores and reasons below it.
- Study signal breakdown and annotations: Review the six signal cards and the annotated text to see exactly which phrases and words triggered the AI detection.
Limitations and Accuracy
What This Tool Does Well
The detector performs best on clearly AI-generated text (especially from ChatGPT and similar models when used without significant prompting toward brevity or informality), on texts over 200 words, and on formal writing like essays, articles, and reports.
Known Limitations
This tool uses heuristic analysis — it is not trained on AI vs. human datasets and will not achieve the accuracy of specialized ML models. False positives may occur with academic writing, formal business documents, or technical writing that uses the same formal vocabulary patterns. False negatives can occur with AI text that has been heavily edited, paraphrased, or written in a casual style. Always treat the results as one signal among many, not as definitive proof.
Why Is AI Detection Hard?
As AI models become more sophisticated and users learn to prompt them for more natural output, the boundary between AI and human writing becomes increasingly blurred. Watermarking techniques exist but are not yet universal. Heuristic detectors can identify common patterns but cannot reliably catch well-disguised or heavily edited AI output.
Common Use Cases
Educators and Academic Institutions
Screen student submissions for potential AI assistance as part of academic integrity review. Note: always confirm with students and never rely solely on automated detection for academic penalties.
Content Editors and Publishers
Quickly screen submitted articles and blog posts for AI-generated content that may not meet your publication's human-authorship requirements.
Hiring Managers
Check candidate writing samples, cover letters, and assessments for AI generation, especially in roles where writing ability is critical.
Researchers
Study the statistical characteristics of AI-generated text versus human writing to inform your understanding of LLM output patterns.
Frequently Asked Questions
How does the AI Content Detector work?
The detector uses heuristic analysis across six signals: AI signature phrase patterns (like "delve into," "in today's world"), sentence length uniformity measured by coefficient of variation, overuse of formal transition words, passive voice frequency, formal/corporate vocabulary density, and vocabulary diversity (type-token ratio). Each signal contributes to a final 0-100 score.
How accurate is this AI detector?
This tool uses heuristic pattern analysis and is not 100% accurate. It works best on longer texts (200+ words) and performs well at identifying heavy AI use. Lightly AI-edited text, AI text rewritten by humans, or highly technical/academic human writing may produce mixed results. Always use the results as one signal among many, not as definitive proof.
What does the AI Score mean?
The AI Score ranges from 0 to 100. Scores of 0-20 indicate Likely Human writing, 21-40 indicates Mostly Human with minor AI-like patterns, 41-60 indicates Mixed or Uncertain content, 61-80 indicates Likely AI-Assisted text, and 81-100 indicates Very Likely AI-Generated content.
What is the Sentence Analysis Map?
The Sentence Analysis Map is a unique feature that scores each sentence individually for AI characteristics. It displays a visual heat strip showing the entire document at a glance, with each segment colored from green (human-like) to red (AI-like). Below the strip, each sentence is listed with its individual AI score and the specific reasons it was flagged.
Is my text stored or shared?
No. All analysis is performed on our server and the results are returned to you. We do not store, log, or share the text you submit. Your content remains private.
Why does sentence uniformity indicate AI text?
Human writers naturally vary their sentence lengths — short punchy sentences mix with longer complex ones. AI language models tend to produce sentences of more uniform length because they optimize for readability and coherence in a different way. The coefficient of variation (CV) of sentence lengths measures this: a low CV means very uniform sentences, which correlates with AI generation.
Additional Resources
Reference this content, page, or tool as:
"AI Content Detector" at https://MiniWebtool.com/ai-content-detector/ from MiniWebtool, https://MiniWebtool.com/
by miniwebtool team. Updated: Mar 10, 2026