CLEAN TEXT

AI Text Cleaner

Make AI responses feel less like a chat transcript. Remove heavy Markdown formatting, soften list-heavy layouts and trim common chat openings, with your original always available.

Processed on your device
Choose a starting style
Fine-tune cleanup

Numbered steps, checklists and nested lists keep their structure by default. Review punctuation changes and any removed wording before copying. This edits presentation, not facts or tone.

Clear your input to load an example.
From an AI chat, a document or your notes.
A LITTLE TIDIERReady when you are

A clean slate for your words.

Your tidied text will appear here.

Your words. Just better formatted.
Make it your own
✓ Free to use✓ Original text preserved✓ No uploads

Keep the answer. Tidy the presentation.

LLM responses often lean on bold headings, short bullet points and chatty introductions. Choose Light tidy to remove Markdown wrapping, or Natural prose to turn simple bullets into separate paragraphs and remove recognised opening or closing chat phrases. Optional em-dash cleanup gives you another punctuation choice. These are local editing rules: they do not generate new sentences, fact-check text or guarantee a particular AI-detector result.

How to use AI Text Cleaner

  1. Paste your text, or load the example into an empty workspace.
  2. Open “Make it your own” to choose the options you need.
  3. Compare the original and result, then copy or download.

What to expect

Chat-framing removal only matches a small set of whole opening and closing paragraphs, such as “Sure!” and “I hope this helps!” It leaves phrases inside the response alone. Natural prose preserves numbered steps, checklists and nested lists unless you separately turn off list markers. Em-dash replacement is optional because a comma will not fit every sentence; review the result. Code contents, link destinations and reference text remain. Keep Markdown syntax disables paragraph conversion for lists.

Works with up to 250,000 characters. Input remains in this page’s memory until you clear, reload or leave it. Word counts use whitespace-separated words and are approximate for languages without spaces.

Examples you can check

These built-in examples use the settings described below. Visible Unicode markers appear only in these explanations.

Chat framing and numbered steps

Natural prose removes recognised boundary chat paragraphs and simple bullet markers. Numbered steps retain their order.

Input

Sure!

## Update

- The draft is ready.
- The references are attached.

1. Review the draft.
2. Approve the release.

I hope this helps!

Expected text output

Update

The draft is ready.

The references are attached.

1. Review the draft.
2. Approve the release.
Try this example in the tool →

Punctuation with protected code

Em-dash replacement is opt-in. Code and blockquote punctuation remain; Markdown markers are removed. Review whether each comma fits the sentence.

Input

A useful change—when reviewed.

`a—b`

> A quoted—phrase

Expected text output

A useful change, when reviewed.

a—b

A quoted—phrase
Try this example in the tool →

Explore all text-cleanup test cases · How we test these tools

Another way to tidy.

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