Claude tone analyzer
What the Claude tone analyzer does
Paste a Claude reply, an email draft or a page of copy into the Claude tone analyzer and press Analyze. What comes back is written analysis: which passages set the register, where it does not match the situation, and what a phrase communicates beyond what it literally says.
This is a server tool. Your text is sent to our AI server to run, which the widget states under the buttons. You get 5 free runs in any rolling 24 hours, the box takes 1 to 12,000 characters, and there is nothing to sign up for. The widget shows how many runs you have left, and the time your allowance resets once they are gone.
One note on the term. Tone analyzer also means guitar amps and audio software. This tool reads written text only and has no audio input.
The Claude tone
What Claude tone actually sounds like
People come here because something in the draft reads as not quite theirs and they cannot point at it. The recurring descriptions of Claude's default register are specific enough to check by hand.
- The trailing hedge
- A clear statement followed by a qualifier that takes some of it back. Writing guides quote "however, it's worth noting" as the shape of it. The claim survives, the confidence does not.
- The pleasantry opener
- The message starts with warmth instead of the point. "I hope this email finds you well" is the stock example. A reader in a hurry reaches paragraph two before learning what you want.
- Both sides, every time
- Acknowledging uncertainty and presenting several perspectives is useful in analysis and costly in a decision email, where it reads as a refusal to recommend anything.
- More context than asked for
- Extra background arrives whether or not it was wanted. It is not wrong, it just buries the sentence that matters.
- The closing offer
- A final line volunteering to do more work. Harmless once. In a thread of five replies it reads as filler.
How to
How to run the Claude tone analyzer in three steps
Paste the whole message, not just the paragraph you are worried about. The opener and the sign off carry more tonal weight than the middle, and are usually the part doing the damage.
- Step 1
- Paste the text. Anything from 1 to 12,000 characters. The meter above the box counts characters and words as you type.
- Step 2
- Use the instruction box if the situation matters. It takes 300 characters. Say who reads this and what mood they are in, because the same sentence lands differently on a calm reader than an annoyed one.
- Step 3
- Press Analyze, read the passages it names, and edit those. Copy the result with the button if you want to keep it. The run counter tells you what is left.
The output
What you get back, and what you do not
You get prose in a read-only box, and you can copy it. That is the whole output. Most tools competing for this term work the other way: one names up to 28 emotional tones, breaks the text down sentence by sentence and prints a confidence percentage, calling anything above 70 percent a strong signal.
This tool has no tone list, so it never picks a tone from a fixed set. It scores nothing, because nothing on this route calculates a number. It does not mark up your text sentence by sentence, because it never splits your text into sentences. What it gives instead is the reason a passage reads the way it does.
The report has a ceiling of 1,400 tokens, so a long input gets a report on the passages that matter rather than a line by line pass. That is why a 12,000 character paste can come back shorter than you expected.
Consequences
What the wrong tone actually breaks
Tone problems do not look like errors. Spell check passes, grammar check passes, every sentence is correct, and the reply you get back is colder than you expected.
A hedged recommendation gets escalated to someone else, because nobody can tell what you advised. A cheerful sign off on an outage notice reads as though you have not understood what happened. A three paragraph preamble in a message asking for a deadline extension gets skimmed and answered no. None of these are faults a correctness tool can see.
The cause
Why Claude output settles into one register
A model trained to be broadly acceptable drifts toward the register least likely to offend anyone: even sentence lengths, softened claims, a warm close regardless of the news. It comes out the same for a product launch and an apology.
That is why the text reads as insincere rather than rude. The tone is not tracking the content. Readers notice the mismatch between the news and the voice delivering it long before they can say what is wrong with it.
The honest answer
Does this prove Claude wrote the text?
No, and it will not say that it does. The analyzer is instructed never to claim certainty about authorship or about which AI model wrote something, and to describe observable signals and limitations instead. That instruction is part of how the route runs.
Plenty of careful human writing hedges and opens with a pleasantry, and plenty of edited Claude output does neither. We make no prediction about what any detector will say, and we have no affiliation with Anthropic or any detection service.
In practice
Who uses the Claude tone analyzer, and when
Anyone about to send something they did not write from scratch. A support agent checking that a drafted apology sounds like one. A manager who wants to know whether feedback reads as encouragement or as a warning. A freelancer checking that a client update sounds confident rather than apologetic.
The common thread: the text is already correct and the sender is unsure how it will land. Run it before you send, and edit the passages the report names rather than rewriting the whole thing.