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AI Content Detector Helper
A transparent, in-browser estimate of how 'AI-like' text looks, from sentence-length variation and vocabulary diversity — a hint, never proof.
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Quick Answer
This AI Content Detector Helper estimates how 'AI-like' a passage looks using two open signals: how much your sentence lengths vary (burstiness) and how often words repeat (vocabulary variety). It combines them into a 0-to-100 score and a plain leaning. It is a transparent heuristic, not a real detector — it uses no trained model, and even purpose-built detectors are unreliable, so the result is a hint and never proof of authorship.
What the AI Content Detector Helper Does
It gives you a quick, see-the-maths read on whether writing looks uniform and repetitive (which can read as machine-generated) or varied (which tends to read as human). It shows the score, the leaning, and the two raw figures behind them.
What it does not do is matter just as much: it does not decide who or what wrote the text. It is a writing-rhythm indicator built from surface statistics, offered so you can understand the signals rather than trust a black-box verdict.
How It Works
As you paste text, it splits it into sentences, measures the spread of sentence lengths and the ratio of unique words, and prints a leaning that updates live.
The whole calculation is an open formula running in your browser. There is no language model, no remote API and no training data — which is exactly why it is honest about being a rough estimate.
What it checks & how
- Split into sentences. It needs at least two sentences to work. It measures how many words are in each one.
- Measure burstiness. It calculates the standard deviation of the per-sentence word counts. Human writing tends to mix short and long sentences (high variation); formulaic text is more uniform (low variation).
- Measure vocabulary variety. It divides the number of unique words by the total word count — the type-token ratio. Repetitive wording lowers this figure.
- Score and label. It combines the two into a number from 0 to 100 and prints a leaning — AI-like, mixed or human-like — alongside the raw figures, updating live. It states plainly that this is a heuristic estimate, not a verdict.
How the heuristic score is computed
Sentence variation (burstiness) = standard deviation of words per sentence
Vocabulary variety = unique words ÷ total words
Score = 100 − (variation × 6) − (variety × 40), clamped to 0–100
Verdict: above 60 leans AI · 40 to 60 mixed · 40 or below leans humanWorked example
'The tool is fast. It is private. It is free.' → variation 0.5, vocabulary 70%, score 69 → leans AI-like (uniform short sentences)The 6 and 40 weights are arbitrary tuning, not a validated model — which is one more reason to treat the number as a loose hint.
Privacy
Your text is analysed locally in your browser. Nothing you paste is sent to a server, stored or logged.
There is no account and no history — refresh the page and the analysis is gone. It is safe for unpublished drafts and confidential work.
Technical Details
| Method | Sentence-length variation plus vocabulary diversity |
|---|---|
| Signals used | Burstiness (standard deviation) and type-token ratio |
| Score range | 0 to 100, with a three-band verdict |
| Minimum input | At least two sentences |
| Model | None — a transparent formula, not a trained classifier |
| Processing | 100% in-browser, live |
Standards & references
- Perplexity and burstiness — The two signals popularised by GPTZero. Perplexity measures how predictable the words are; burstiness measures how much sentence length and complexity vary. Human writing is typically more bursty.
- Detector reliability — OpenAI withdrew its own AI Text Classifier in July 2023 for low accuracy — it correctly caught only 26% of AI text and falsely flagged 9% of human text.
- Bias against non-native writers — A Stanford study found detectors labelled 61% of TOEFL essays by non-native English speakers as AI-generated, which is why universities such as Vanderbilt and Pittsburgh disabled them.
Accuracy & Limitations
This is not a definitive detector, and no honest tool can be. It does not read meaning or use a trained language model. It measures only two surface signals — how much your sentence lengths vary and how often words repeat — so it is a rough indicator, never proof.
Even purpose-built, commercial detectors are unreliable. OpenAI retired its own classifier in 2023 after it caught barely a quarter of AI text and flagged genuine human writing as fake. Treat any AI-detection result, including this one, as a weak hint.
It can be wrong both ways. Terse, repetitive human writing — a checklist, a beginner's essay — can score AI-like, while edited or deliberately varied AI text can score human-like. Short inputs are especially unstable.
The vocabulary measure naturally falls as text gets longer, so a long human passage can drift toward an AI-like score for reasons that have nothing to do with how it was written.
Never use this to accuse a student, writer or employee. Detectors are known to be biased against non-native English speakers, and a false accusation does real harm.
Real-World Use Cases
A quick self-check
Paste your own draft to see whether it reads as uniform or repetitive, then add sentence-length variety. That is useful editing feedback regardless of how the text was written.
Teaching what burstiness means
Show students why varied sentence rhythm matters, using a transparent formula instead of a black-box score.
Editing for natural rhythm
If everything scores uniform, it is a nudge to break up same-length sentences — good prose advice on its own.
Understanding detector limits
See, in the open, how crude the underlying signals are and why AI-detection results should not be trusted as evidence.
When to use it — and when not to
Good for
- A rough, transparent feel for how varied your writing is
- Learning what burstiness and vocabulary diversity mean
- Self-editing your own draft for sentence-length variety
- Seeing why AI detectors are unreliable
Not the best choice for
- Proving whether text was written by AI
- Any decision about academic integrity or employment
- Judging non-native or short text fairly
- A defensible or accurate detection result
There is no reliable way to prove AI authorship from text alone — even leading commercial detectors get it wrong. Use this only as a writing-rhythm hint, never as evidence.
Frequently Asked Questions
Can this prove my text was written by AI?
No. It is a transparent heuristic based on surface statistics, not a real detector. It can never prove authorship, and you should not treat its result as evidence.
How does it decide?
It measures two things: how much your sentence lengths vary (burstiness) and how many of your words are unique (vocabulary variety), then combines them into a score from 0 to 100.
What is burstiness?
It is the variation in sentence length and complexity. Human writing tends to be bursty — short punchy sentences mixed with long winding ones — while machine text is often more uniform.
What does vocabulary variety mean?
It is the ratio of unique words to total words, also called the type-token ratio. Heavy repetition lowers it; varied wording raises it.
Are AI detectors accurate?
No, and that is well documented. OpenAI shut down its own classifier in 2023 for low accuracy, and independent studies show frequent false positives, especially on non-native English writing.
Why did my own human writing score AI-like?
Uniform sentence lengths or repeated wording push the score up. Longer text also lowers the vocabulary figure on its own, which nudges the result toward AI-like.
Why did AI text score human-like?
Varied or edited AI text raises burstiness and vocabulary variety, which moves the score toward human. That is exactly why the signals are unreliable.
Should teachers use this to catch cheating?
No. Detectors are biased against non-native speakers and produce false positives; a wrong accusation causes real harm. This tool is for understanding writing rhythm, not for discipline.
Does longer text change the score?
Yes. The vocabulary-variety figure tends to fall as text gets longer, so the same writing can score more AI-like simply because it is long.
How much text do I need?
At least two sentences. More text gives a steadier reading, but the result is still only a hint at any length.
Is my text sent anywhere?
No. The analysis runs entirely in your browser. Nothing you paste leaves your device.
Is it free?
Yes, completely free with no sign-up and no limits.
References
Documented against this tool's own code: it scores text only from sentence-length variation and the unique-to-total word ratio, with no trained model behind it — which is exactly why the page treats every result as a hint, not a verdict.
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Ready to try the AI Content Detector Helper?
It is free, private and runs entirely in your browser — no sign-up, no uploads, no limits.