LinkedIn Post Cleaner

Paste your AI-polished draft on the left. Get clean text on the right - with invisible watermark characters and AI typographic tells stripped out. Everything runs in your browser; nothing is uploaded.

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Why this works — the research behind it

Newer LLMs leave two kinds of footprints, and this tool targets both:

  • Invisible Unicode artifacts. Through 2025, ChatGPT models were observed emitting hidden characters — the narrow no-break space (U+202F), zero-width space (U+200B), em space (U+2003) and em dash (U+2014). Forensic analysis concluded these are most likely training artifacts from professionally typeset text rather than a deliberate watermark, but either way they flag text as machine-touched. (Rumidocs, analysis)
  • Statistical & stylometric tells. Modern detectors don't rely on hidden characters alone — they weigh punctuation frequency, sentence burstiness and lexical patterns, and treat homoglyph substitution as an adversarial signal (Mikros, 2025; Kanwal et al., 2026). Normalizing curly quotes, em-dashes, exotic spaces and lookalike letters reduces those surface tells.
  • What a cleaner can't fix. Token-level statistical watermarks and embedding-based classifiers key on word choices, not characters — only genuine rewriting changes those. This tool removes the mechanical fingerprints; your own voice does the rest.