Most tone checkers never check your tone

I ran the same question through three AI research agents recently: what are the best tone checkers right now? Claude, ChatGPT and Gemini each came back with a long, confident report. They disagreed on plenty, cited some sources that don’t exist, and one of them invented a charming origin story about my own company. So I did what I keep telling people to do with AI research. I kept the structure, traced every claim back to a primary source, and cut whatever didn’t survive contact with reality.

This is the merged, verified version. Sixteen tools, sorted by the job they actually do, with the receipts numbered at the bottom.

The bias card, face up: I co-founded one of these tools

Subtext is my company, and it appears in this post. Weigh everything I say about it accordingly.

To keep this useful anyway, I held my own product to the same standard as everyone else’s: claims come from product pages, documentation, app store listings or peer-reviewed research, and each one links out with a numbered source. Where a claim only exists in a vendor’s marketing, I say so. And I cut what the AI agents confidently reported but no source supports, including that flattering origin story (a “former therapist” supposedly built Subtext; nobody did, Anton is an engineer and I do the words).

A real tone checker diagnoses before it rewrites

Every tool in this space gets called a tone checker, but there are two different jobs hiding under one label.

Diagnosis tells you how your text currently reads. Rewriting changes it into something else. The difference sounds academic until you look at a real draft. Take “Fine. Do whatever you want.” A rewriter will happily turn that into “Sounds good, go ahead with whichever option works best.” A diagnostic tool stops you first: “Fine.” reads as clipped, “whatever you want” reads as withdrawal, and the whole thing lands as passive when you probably meant tired. Once you see that, you can decide what to do about it. Maybe you soften it. Maybe you meant the edge and keep it.

The rewrite-only tools skip that step. They give you a nicer sentence without ever telling you what was wrong with yours, which is how people end up sending polished messages that still say the wrong thing. So that’s how I’ve sorted the field: tools that read first, tools that only rewrite, and tools that tune your tone to one specific audience.

You think your tone lands 78% of the time. It lands 56%.

Before the tools, the reason they exist.

In 2005, Justin Kruger, Nicholas Epley and colleagues published five experiments on tone in email¹ in the Journal of Personality and Social Psychology. In one study, senders predicted their tone (serious or sarcastic) would come through about 78% of the time. Receivers actually got it right 56% of the time², barely better than a coin flip, and the receivers felt nearly as confident as the senders. The authors’ diagnosis, in their own words¹:

This overconfidence is born of egocentrism.

You hear your own message with the full soundtrack of your intentions. Your reader gets the words on a screen.

Twenty years later that finding is the quiet business model of every tool below.

Four tools that read your tone before touching a word

Subtext

Subtext is the tool I co-founded, built for personal messages rather than documents. You paste a draft, drop in a screenshot of the conversation, or record a voice note, and it reads the whole exchange before saying anything. It marks the exact words that could feel harsh, passive or easy to misread, then names the feeling underneath³. After the read, one-tap adjustments (Warmer, Shorter, More casual, Add confidence)⁴ rewrite the message while keeping your phrasing as the starting point, and it never sends anything for you.

The store listing is blunt about who it’s for: people who rewrite the same message five times before sending, overthinkers, and anyone wondering “does this sound okay?”⁴. A lot of the warmest reviews come from neurodivergent users, especially ADHD users who feed it long, chaotic drafts and get back something clear that still sounds like them⁵. It runs on iOS, Android and a synced web app, in more than a dozen languages written natively rather than translated. Free to try, then a subscription unlocks the rest. Two honest limits: it’s built for messages, so long-form documents belong elsewhere, and its own terms say plainly that it’s a communication assistant, not therapy⁶, and that your texts aren’t used to train AI models.

Grammarly’s tone detector

Grammarly runs the most widely deployed tone diagnosis in the world. It identifies the tone of your writing from word choice, phrasing, punctuation and even capitalisation⁷, using a combination of rules and machine learning⁸. When it launched in 2019 it could name about 40 tones, from friendly and joyful to aggressive and annoyed⁹. It needs a bit of text to work with: around 150 characters in the browser¹⁰, 90 on the mobile keyboard¹¹. The labels are the diagnosis; sentence-level tone rewrites sit in the paid tiers. For companies, Grammarly Business adds brand tones: admins pick from more than 50 tones and mark them on-brand or off-brand¹², and everyone gets nudged in real time. If your writing lives in documents and work email, this is the benchmark.

Goblin Tools (the Judge and the Formalizer)

Goblin Tools is a collection of tiny free AI tools by Belgian developer Bram De Buyser, described on its own site as “small, simple, single-task tools”¹³ built mostly for neurodivergent people. Two of them matter here. The Judge senses the mood or emotion behind any message you’ve received, and the Formalizer instantly rewords your text for the right tone¹⁴, with a “spiciness” dial for how much it changes. That receive-side decoder is genuinely rare; almost everything else in this post only looks at what you’re sending. The website is free and the mobile apps are cheap one-off purchases.

Sapling

Sapling is aimed at customer support and sales teams, and it publishes the most transparent tone taxonomy in the group. Its free tone checker identifies more than 25 emotional tones (joy, confusion, gratitude, fear) at both sentence and document level¹⁵, and the developer API covers 28 tones with per-sentence probabilities¹⁶. If you want tone detection inside your own product rather than an app, this is the practical successor to the old IBM API we’ll bury in a minute.

Seven tools that rewrite into whatever tone you pick

These are useful and I use some of them, but none of them will tell you how your original draft reads. They hand you a different draft.

Apple Intelligence Writing Tools sit at the system level and rewrite selected text to be more professional, friendly, or concise, nearly everywhere you can type including third-party apps¹⁷, plus a free-form “describe your change” box¹⁸. Free with iOS 18.1, iPadOS 18.1 or macOS Sequoia 15.1 on supported hardware. Three presets, zero diagnosis.

Microsoft’s Copilot does the equivalent inside Office: select text in Word, choose Rewrite, and use the Adjust Tone menu (Neutral, Casual and Concise among the options)¹⁹. You need a Copilot licence, and again it changes tone without ever naming yours.

Wordtune is the quickest of the dedicated rewriters: highlight a sentence, tap Casual or Formal, plus Shorten and Expand²⁰, and pick from the suggestions. Free tier, with paid plans from about $7 a month billed annually²¹, as of August 2026.

Hemingway Editor built its name on readability, colour-coding dense sentences and passive voice, which is adjacent to tone rather than tone itself. The paid Hemingway Editor Plus adds AI rewriting, including adjusting selected text to be more professional or friendly²² and dedicated more casual, more formal and more persuasive tools²³. Still the best cure for bloated prose I know.

Three quick ones. LanguageTool is the multilingual pick, a grammar and style checker in around 30 languages with a paraphraser in the paid tier; tone is a side effect here, not the product. ProWritingAid is for long-form manuscripts, a deep stack of style and readability reports rather than a live read on how a text message will land. And QuillBot is the students’ paraphraser with preset modes, Formal among them; it rewrites fluently and tells you nothing about your original.

Four tools that tune your tone to one specific reader

This group answers a different question: how should I sound to this specific person, or as this specific company.

Crystal profiles your recipient with the DISC personality framework, then its Writing Assistant checks the words, phrases, style and tone of your email in real time inside Gmail or Outlook and steers you toward that person’s communication style²⁴. It’s slightly unsettling and occasionally brilliant, and it was very clearly built for sales.

Lavender is a cold-email coach: it scores every draft from 0 to 100 as you write, with tone among the factors, and suggests fixes tied to reply-rate data²⁵. There’s a free tier of 5 emails a month, then plans from $29 a month (as of August 2026)²⁵. If your job is outbound, the score becomes a habit fast.

Textio²⁶ owns the hiring niche, flagging biased or exclusionary language in job posts and performance feedback and scoring how the language will land with candidates. And Writer works at enterprise scale: upload writing samples and it builds a voice profile²⁷ so a whole organisation’s AI output stays in one tone.

The free single-page checkers are fine, with one caveat

Beyond the big names sits a long tail of free paste-your-text-here pages. Sapling’s free checker (above) is the credible one. LiveChatAI’s tone checker²⁸ identifies a dominant tone and highlights which phrases drove the verdict, detection only, no rewrites. AskAI’s version²⁹ wraps a chat model around a 0 to 100 formality score and flags tone drift across long documents, with a paid tier for heavier use. Fine for a blog paragraph or a cover letter.

The caveat: anything you paste into a free web page travels to someone’s server, and most of these pages say little about what happens next. I’d paste a marketing paragraph in without a second thought, and I’d keep a breakup text well away from them.

The tone API everyone used to cite is dead

For a decade, “tone checking” in the technical sense meant one thing: IBM Watson Tone Analyzer, the API behind countless demos and research papers. It’s gone. IBM announced the deprecation on 24 February 2022, and the service shut off on 24 February 2023³⁰. What remains is a small pre-built tone classification model inside Watson’s Natural Language toolkit³¹, covering English and French with a short list of categories such as excited, frustrated, impolite, polite, sad, satisfied and sympathetic.

I include the obituary because it explains the market. The standalone tone API era ended, and the energy moved into the assistants above and into large language models that rewrite anything on demand. Which brings us to the uncomfortable part.

What the research says about letting AI touch your words

The rewriting part is now trivial. The consequences are less tidy, and there’s a real literature on them.

Researchers call it AI-mediated communication: when an AI system modifies, augments or generates messages between people³², as Jeff Hancock, Mor Naaman and Karen Levy defined it in 2020. The headline finding came a year earlier: in a CHI study of Airbnb host profiles, text that readers believed was AI-written was rated less trustworthy³³. A follow-up study of AI smart replies found the suggestions changed the language people actually produced, nudging it toward the positive, and shifted how conversation partners perceived each other³⁴.

There’s also a bias problem in the models themselves. A 2025 study out of Monash University generated thousands of assistant dialogues from deliberately neutral prompts and found a consistent skew: the models default to sounding, in the researchers’ words, “overly polite, cheerful, or cautious even when neutrality is expected”³⁵, with tone classifiers detecting the skew at macro-F1 scores up to 0.92³⁵. In plain terms, the machines have an accent. If you let one rewrite everything you send, you start speaking with that accent too. The NLP field even has a name for the machinery underneath, text style transfer, with a whole survey literature³⁶, and none of it is trained on what makes you sound like you.

My conclusion from all of this, and yes, notice whose conclusion it is: use these tools as a mirror first and a ghostwriter rarely. A tone read before sending fixes the 78/56 problem from the Kruger study. A full rewrite of everything you send creates a new problem, the one where your mum can tell a robot answered her.

How I’d choose

For personal messages and hard conversations, the honest shortlist is Subtext or Goblin Tools. Subtext if you want the diagnosis, the rewrite and the conversation context in one place with your voice preserved; Goblin’s Judge and Formalizer if you want free, single-task and no account. For documents and work email, Grammarly’s detector is the benchmark, with Hemingway as the edit for bloat. If you already live on Apple or Microsoft hardware, the built-in rewriters cover preset tone shifts at no cost, and you only pay for a dedicated tool when you need actual diagnosis. For sales outreach take Lavender, for recipient-tuned messages Crystal, for hiring language Textio, and for company-wide brand voice Writer. Broke and curious? Sapling’s free checker plus Goblin Tools will teach you the concept for nothing.

And whichever one you pick, keep the last word. The research above is fairly clear that the goal is a message that sounds like you on a good day, not like a model with impeccable manners.

If the “does this sound okay?” moment is the one you know too well, that’s the exact moment Subtext was built for. It reads the tone first and helps you fix what could land wrong, in your own words.

---

I merged three AI research reports for this post and cut what didn’t check out, but I won’t pretend the survivors are beyond argument. If you make one of these tools and think I’ve sold yours short, or you know a checker that diagnoses better than the four I found, tell me and I’ll test it and update the post.

Samet Durgun is the co-founder of Subtext, an app that catches the emotional tone of your messages and rewrites them in your own voice. He’s based in Berlin.

Sources

Every link above goes to the primary source where one exists. The citations are numbered below, in order of appearance.

Why tone breaks

1. Kruger, J., Epley, N., Parker, J., and Ng, Z. (2005). Egocentrism over e-mail: can we communicate as well as we think? Journal of Personality and Social Psychology, 89(6), 925-936. DOI: 10.1037/0022-3514.89.6.925. Open PDF: web-docs.stern.nyu.edu
2. American Psychological Association, Monitor on Psychology (February 2006). E-mails and egos. apa.org

The tools

3. Subtext, official site. subtext.it (feature descriptions and trigger count)
4. Subtext: AI Writing Assistant, Apple App Store listing (features, audience, in-app subscription prices). apps.apple.com
5. Subtext: AI Writing Assistant, Google Play listing (use cases and user reviews). play.google.com
6. Subtext, Terms and Privacy. subtext.it
7. Grammarly, Writing Tone Detector and Tone Suggestions. grammarly.com
8. Grammarly blog, Meet Grammarly’s Tone Detector. grammarly.com
9. VentureBeat (24 September 2019). Grammarly uses AI to detect the tone and tenor of your writing. venturebeat.com
10. Grammarly Support, Using the tone detector in the browser extension. support.grammarly.com
11. Grammarly blog, Tone Detector for Mobile. grammarly.com
12. Grammarly Business, Brand Tones. grammarly.com
13. goblin.tools About, quoted via Autism Community Training. actcommunity.ca
14. Goblin Tools, official Google Play listing. play.google.com
15. Sapling, Tone Checker / Detector. sapling.ai
16. Sapling, Tone Detection API documentation. sapling.ai
17. Apple Support, How to use Writing Tools with Apple Intelligence. support.apple.com
18. Apple Support, Use Writing Tools on Mac. support.apple.com
19. Microsoft Support, Elevate your content with Copilot in Word. support.microsoft.com
20. Wordtune, Free Online Rewriting Tool. wordtune.com
21. Capterra, Wordtune pricing (secondary; prices as of August 2026). capterra.com
22. Hemingway Editor Help, Rewriting text with AI tools. hemingwayapp.com
23. Hemingway Editor blog (5 March 2024). Announcing powerful AI tools for adjusting tone and style. 4.hemingwayapp.com
24. Crystal, Getting Started with the Crystal Writing Assistant. crystalknows.com
25. Woodpecker (2026 review; secondary, prices as of August 2026). Lavender AI Review. woodpecker.co
26. Textio, official site (augmented writing for hiring; bias and tone guidance). textio.com
27. Writer, Introducing voice. writer.com
28. LiveChatAI, Free AI Tone Checker. livechatai.com
29. AskAI, AI Tone Checker. askai.free
30. IBM Watson SDK deprecation notice (Tone Analyzer deprecated 24 February 2022, withdrawn 24 February 2023). cocoapods.org
31. IBM, Watson Natural Language Processing tone classification block. dataplatform.cloud.ibm.com

Writing with AI

32. Hancock, J. T., Naaman, M., and Levy, K. (2020). AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations. Journal of Computer-Mediated Communication, 25(1), 89-100. academic.oup.com
33. Jakesch, M., French, M., Ma, X., Hancock, J. T., and Naaman, M. (2019). AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness. CHI 2019. dl.acm.org
34. Mieczkowski, H., Hancock, J. T., Naaman, M., Jung, M., and Hohenstein, J. (2021). AI-Mediated Communication: Language Use and Interpersonal Effects in a Referential Communication Task. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1). dl.acm.org
35. Bodara, H., Mushfiq, M. M., and Siddiqui, I. F. (2025). Bias Beneath the Tone: Empirical Characterisation of Tone Bias in LLM-Driven UX Systems. UISE ’26 workshop (ACM). arxiv.org
36. Jin, D., Jin, Z., Hu, Z., Vechtomova, O., and Mihalcea, R. (2022). Deep Learning for Text Style Transfer: A Survey. Computational Linguistics, 48(1), 155-205. direct.mit.edu