The tool
What the Claude style analyzer does
Paste text and the Claude style analyzer describes how it reads: the register it sits in, how much the sentence lengths vary, which constructions repeat, where the tone shifts between one section and the next. What comes back is written analysis in plain sentences.
It is not a scorecard. There is no readability index, no word cloud and no percentage. Most style tools give you numbers, and numbers are useful when you want to compare two drafts. This gives you a reading, which is more useful when you want to know what to change.
The output
What a style analysis actually tells you
The analysis is written for your text rather than filled into a template, so the emphasis shifts with what is actually notable. These are the angles it works from.
- Register
- Where the writing sits between formal and conversational, and whether it stays there throughout.
- Sentence shape
- Whether lengths vary or settle into one rhythm, which is the single most visible style habit in AI drafts.
- Repetition
- Constructions, openers and connective phrases that recur often enough for a reader to notice.
- Tone consistency
- Where a section reads differently from the rest, which is usually where two drafting sessions were joined.
- Vocabulary level
- Whether the word choice matches the audience the text seems to be addressing.
How it works
How to analyze Claude writing style in three steps
It is a server tool: your text is sent to our AI server, analysed there and returned.
- Step 1
- Paste the text. Anything from one sentence up to 12,000 characters, which is roughly two thousand words.
- Step 2
- Optionally add an instruction of up to 300 characters, such as focus on tone consistency between sections. Then run it.
- Step 3
- Read the analysis and fix one thing at a time. Your remaining runs from the five show on the button.
Steering it
Asking the analyzer one specific question
A general analysis of a long text spreads itself thin. The instruction field, capped at 300 characters, narrows it to whatever you actually care about, and this is the single biggest improvement you can make to the result.
Instructions worth typing: compare the first half to the second, tell me if this matches a technical audience, focus only on sentence variety, identify which paragraphs read as written by someone else.
Scope, stated honestly
What this analyzer does not measure
No readability formula. Flesch-Kincaid, Gunning-fog, SMOG and the rest are not computed here, so if you need a grade-level number for a compliance requirement, this is not the page for it.
No word-frequency table, no word cloud, no lexical density figure, no parts-of-speech breakdown and no passive-voice tagging. It also does not check grammar or spelling, and it will not tell you who wrote the text. Nothing about a writing style is proof of authorship, and this tool does not claim otherwise.
The free alternative
The deterministic check that costs no runs
If what you want is repeatable rather than interpretive, the watermark scanner on this site flags 17 named writing patterns: the scene-setting opener, the empty hedge, the formal connector, the overused verb, the hype adjective, the negation pivot and eleven more. It highlights each one in place and explains why it is flagged.
That check runs in your browser, uploads nothing and has no limit, so you can run it on every draft. Use it for the mechanical tells and use this analyzer for the judgement calls it cannot make.
The cause
Why Claude drafts drift in style
A long piece assembled over several prompts carries the seam. Each request arrives with slightly different framing, and the model matches the framing it was given, so the register moves between sections in a way the author stops noticing after the third read.
Within a single response, the drift is usually toward evenness: similar sentence lengths, similar paragraph shapes, the same connective vocabulary. That regularity is what a reader registers as machine-written, and it is the thing an analysis is most useful at naming.
Who it's for
Who uses a Claude style analyzer, and when
Writers checking a draft against the voice they meant to write in, before an editor does it for them. Content teams keeping a set of pages sounding like one publication rather than six contributors.
Students use it on their own writing to find where their voice slipped, subject to whatever their institution's policy says about AI assistance.