AI Writing Style Analyzer
See your text's stylistic signals — sentence-length variation, repeated phrasing, generic transition words — honestly, with no fake pass/fail verdict.
How to use — AI Writing Style Analyzer
- Paste at least a few paragraphs of text.
- Click Analyze text — see objective stylistic signals: sentence-length variation, repeated phrasing, generic transitions and vocabulary variety.
- Read the signals as clues, not a verdict — human writing can score "AI-like" and AI writing can score "human-like" depending on style and editing.
FAQ
Why doesn't this give a simple "% AI" score like other detectors?
Because that number is misleading. Independent research and even universities (several have dropped Turnitin's AI score and similar tools) have found these detectors produce meaningful false positives, especially against non-native English writers and heavily-edited text. A confident-looking percentage hides that uncertainty — we'd rather show you the actual signals than a fake-precise number.
What is "burstiness" and why does it matter?
Human writing naturally mixes short punchy sentences with long complex ones — high burstiness. Unedited AI text often has more uniform sentence lengths — low burstiness. It's a real, measurable pattern, but heavily-edited AI text or a very consistent human writer can both land anywhere on this scale — it's a clue, not proof.
What do repeated phrases and generic transitions indicate?
AI text sometimes leans on the same connecting phrases repeatedly ("Moreover," "In conclusion," "It is important to note that"). Finding several isn't proof of AI — some human writers do this too, especially in formal or academic writing — but a heavy concentration is worth a second look.
Should I use this to accuse someone of using AI?
No. Please don't use signal-based tools like this (or any AI detector) as the sole basis for academic or professional accusations — the false-positive risk is real and well documented. Use it for your own writing, to understand your own patterns, or as one small data point among many.