Email Text Cleaner

Hidden Unicode breaks preheaders, breaks link tracking, and truncates subject lines. Clean AI newsletter copy before your ESP paste.

Your Text

0 / 500 words · 20 of 20 checks left this hour ·

Your text is processed on our server to generate results. We do not store the content of your text.

Need to pass AI detection?

This tool strips hidden Unicode characters. To address deeper AI writing patterns, use our humanizer or run a full AI scan on the home page.

Humanize Your Text

What are AI Watermarks?

Unicode Watermarks

AI systems may embed invisible Unicode characters in generated text to identify AI-produced content.

Character Detection

Our tool detects and categorizes invisible watermark characters by type.

Why email clients amplify invisible bytes

ESP HTML compressors and Gmail clipping rules count bytes you cannot see. A zero-width space in a subject line can truncate preview text or break personalization tokens.

Newsletter writers assembling AI drafts should clean before dropping into Mailchimp, Klaviyo, Beehiiv, or Substack editors.

Email is a byte-counting medium. Gmail clips messages over 102KB of HTML. ESPs enforce subject line character limits for mobile preview. Preheader text competes with invisible boilerplate for the same preview slot. A zero-width space does not display, yet it consumes bytes and can push visible copy past clipping thresholds.

Personalization engines merge tokens like {{ first_name }} by exact string match. Hidden Unicode inside merge tags or fallback values causes silent failures — subscribers see blank greetings while your dashboard reports successful sends. Cleaning AI-generated personalization snippets before ESP paste eliminates that entire failure class.

Cold outreach teams pasting AI personalization into Gmail or Outlook hit the same wall. Mail merge add-ons and CRM snippets copy contaminated strings from chat tools. Recipients never see the bug; your reply rates drop because broken tokens make messages feel robotic or incomplete.

Subject, preheader, and body workflow

Clean each micro-field separately. Subject and preheader are highest risk because character limits are tight. Body paste can wait, but links in the body still fail when U+200B sits inside href text.

Treat subject, preheader, and body as three separate paste operations. AI tools often generate all three in one response; copy each field individually into this cleaner before moving to your ESP. Subject lines with hidden bytes truncate early in iOS Mail; preheaders with U+200B can disappear entirely behind preview deduplication logic.

Body copy carries link-tracking risk. UTM parameters and merge-wrapped href values must match exactly when the ESP rewrites URLs. A zero-width space inside anchor text or inside the href itself produces links that look clickable yet 404 or strip tracking on click.

Button modules in drag-and-drop builders are not safer than raw HTML. Marketing teams paste AI CTA copy into Mailchimp buttons; Klaviyo hero blocks; HubSpot rich text. Each module stores the string you pasted — invisible bytes included — in the campaign JSON your ESP sends at scale.

A/B tests comparing subject lines can produce false negatives when one variant carries hidden Unicode and loses not because of copy quality but because of byte-limited preview truncation. Clean both variants before upload so test results reflect messaging, not clipboard contamination.

Plain-text multipart alternatives

Even plain-text parts inherit clipboard Unicode. Cleaning before paste keeps multipart MIME sources aligned.

Multipart MIME messages ship HTML and plain-text alternatives together. Many teams paste AI copy into the HTML editor and assume the plain-text part auto-generates cleanly. Auto-generated plain text often preserves zero-width bytes from the HTML source, producing mismatches that spam filters and accessibility clients notice.

Subscribers on Apple Mail, Superhuman, or plain-text-only clients see the text alternative. Hidden Unicode there can break unsubscribe links — a compliance risk — or truncate transactional tokens in receipts and password resets assembled with AI assistance.

Plain-text cold outreach feels personal precisely because it is simple. Invisible bytes undermine that simplicity. Clean before paste so your one-line AI personalization in a sales email reads exactly as intended when the prospect forwards it to their team.

Newsletter operators exporting archives to Substack, Ghost, or self-hosted systems should clean at composition time. Archive HTML reused in web views and RSS feeds inherits the same bytes your subscribers received. One clean pass at draft time protects web, email, and RSS surfaces simultaneously.

How to clean email text before sending

Checking a piece of AI-generated text for invisible watermarks takes less than a minute:

  1. Copy your AI-generated text. Copy the text you want to clean from your document, AI chat, or clipboard.
  2. Paste into the checker. Paste the text into the input box on this page.
  3. Run the check. Click Check for watermarks. The tool scans for invisible Unicode characters and hidden formatting markers in seconds.
  4. Copy the cleaned output. Review the detection report, then copy the cleaned, watermark-free version of your text.

Unicode problems in email HTML

AI systems can hide two broadly different kinds of signal in their output. Our checker is specifically built to detect and remove the first kind — invisible Unicode characters. The second kind, statistical watermarks, requires rewriting to neutralise.

Invisible Unicode watermarks

These are real characters inserted between visible letters that don't render on screen. They travel with copy-paste, get carried into Word documents, Google Docs and CMS fields, and can fingerprint text back to the model that produced it. The checker scans for:

  • Zero-width space (U+200B)
  • Zero-width non-joiner (U+200C) and zero-width joiner (U+200D)
  • Word joiner (U+2060)
  • Soft hyphen (U+00AD)
  • Variation selectors (U+FE00 - U+FE0F)
  • Left-to-right and right-to-left marks (U+200E / U+200F)
  • Byte order mark / ZWNBSP (U+FEFF)
  • Other non-printing formatting characters commonly used as covert channels

Statistical (cryptographic) watermarks

These are patterns in which words the model chooses. They are imperceptible in any one sentence and only emerge over many words. A Unicode scan cannot remove them — to neutralise a statistical watermark you typically need to lightly rewrite the text. Our guide to natural AI writing techniques covers how to do this without losing meaning.

Frequently asked questions

Will cleaning fix broken merge tags?

If invisible bytes broke the tag syntax, yes. If the ESP field name is wrong, fix the template.

Does this help cold outreach?

Yes. Sales teams pasting AI personalization into Gmail benefit from the same clean pass.

Are emoji in subject lines safe?

Visible emoji remain. Only hidden watermark-class bytes are stripped.

Works with HTML email builders?

Clean text before pasting into any builder’s text or code modules.

Is this watermark checker free?

Yes. You can scan up to 500 words without an account. Sign in for longer documents, full cleaned text, and a character-level breakdown of every hidden marker removed.

Is my text stored when I use the checker?

We process your text only to return a detection report and cleaned output. We do not retain the content of your pasted text for any other purpose.

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