Llama invisible characters
What the Llama invisible character detector does
Paste in text copied out of a Llama-based chatbot and this app finds the zero-width and non-printing Unicode characters sitting inside it, without changing how the text looks. It's built for the question people ask before pasting that output anywhere else: why does this have hidden characters in it, answered with a specific list rather than a vague warning.
It's a server tool, not a browser script. Your text is sent to our AI server to be checked, and you get 5 free checks in any rolling 24 hours. No account, and nothing you paste is needed again once the result comes back.
The characters
The 14 hidden characters this app checks for
Every character checked here is an ordinary Unicode codepoint with a real technical purpose, grouped into seven families:
- Zero-width space (U+200B)
- Occupies a character slot and renders nothing. The single most common invisible marker in copied AI output.
- Zero-width joiners (U+200C, U+200D)
- The non-joiner and joiner, sometimes left over from how rich text renders certain characters and emoji.
- Word joiner (U+2060)
- An invisible joiner that prevents a line break at that point, often near a bolded phrase.
- Byte-order mark (U+FEFF)
- A marker meant to sit at the start of a file, occasionally left mid-response by an export or copy path.
- Soft hyphen (U+00AD)
- Invisible until a line wraps there, then a hyphen appears in a word that never had one.
- Non-breaking spaces (U+00A0, U+202F, U+200A)
- Look identical to a normal space, behave differently in code, slugs and search.
- Bidi controls (U+202A to U+202E)
- Five directional embedding and override characters that can quietly reorder mixed-direction text.
Workflow
How to check Llama text for invisible characters in three steps
No formatting to strip first, nothing to configure. Paste, run, read.
- 1. Copy from the app
- Use whichever app is running Llama and its own copy button rather than selecting text by hand. That's the version most likely to carry hidden characters.
- 2. Run the check
- It goes to our AI server once, gets scanned for hidden Unicode characters, and the result comes back to the page.
- 3. Read what was found
- Each flagged character is listed with where it sits. Nothing about the text changes; this only reports.
Where they come from
Why Llama text carries hidden characters, and why it varies by app
Llama runs inside many different products, Meta's own apps, WhatsApp and Instagram integrations, third-party chatbots and self-hosted playgrounds, each with its own rich-text renderer. Converting that formatting to plain text on copy is where most of these characters slip in, and which ones show up can vary from app to app.
The same kinds of characters show up copying out of a Word document, a PDF or a translated page, none of which involve Llama. Finding one tells you something about that specific copy path, not about who wrote the underlying words.
What a finding actually means
Does finding a hidden character prove Llama wrote the text?
No, and this app won't claim otherwise. A hidden character is a formatting artefact of the copy path, not a fingerprint tied to Llama specifically. The same characters turn up in human-typed documents exported from Word, translated text and PDF copy-paste.
That's separate from a real research area: statistical, token-level watermarking, where a model's word-choice probabilities are tuned in a pattern only a statistical test can see, not inserted characters. No character scan, including this one, can detect that kind of watermark.
Why you might see a flag
Why human-written text can trigger this too
Plenty of ordinary human workflows produce the same characters as a Llama-app copy-paste, so a flag isn't evidence of who wrote the underlying words.
- Messaging app formatting
- WhatsApp, Instagram and other chat apps render rich text of their own and can leave formatting characters behind on copy.
- Translation tools
- Machine and professional translation software frequently leaves directional or joining characters behind.
- PDF copy-paste
- Extracting text from a PDF often introduces stray characters the original document never displayed.
- Other chat interfaces
- ChatGPT, Claude and other assistants render rich text too, and can leave similar characters behind on copy.
- CMS and rich-text editors
- Switching between rich text and plain text views in a CMS is a common source of leftover formatting characters.
Why it matters anyway
What these hidden characters actually break
These characters cause real problems once text moves somewhere that parses it strictly. A zero-width space inside a heading splits a keyword, so a slug and its visible title stop matching. A byte-order mark inside a JSON file breaks the parser, and non-breaking spaces confuse diffing tools.
Pasting straight from a Llama-based app into a CMS, an email or a code editor is exactly where these problems surface. Checking first turns a category of confusing bugs into a non-event.
Who uses it, and the free checks
Who uses this detector, and how many free checks you get
Writers, editors and developers pasting Llama-based output into a CMS, an email or a codebase use this to catch formatting problems before they cause one. It's a server tool: your text travels to our AI server to be checked, which is why there's a limit.
You get 5 free checks in any rolling 24 hours, no account needed. For repeated cleaning with no limit at all, the site's zero-width space remover and watermark cleaner run entirely in your browser instead.