Run most AI-text cleaners on a document with bullet points and you get back a wall of text. The lists collapse, the indentation vanishes, and the code loses its spacing. The fix is a cleaner that understands structure before it touches anything.
Why generic cleaners destroy your formatting
A basic cleaner runs blunt global rules: collapse every run of spaces, strip every line break, replace every character it does not like. Those rules cannot tell the difference between:
- a stray double space in a sentence (noise) and the indentation of a nested list (structure)
- a random blank line (noise) and a paragraph break (structure)
- a smart quote in prose (fine to change) and a quote inside a code block (must not change)
So it flattens everything. One competitor even advertises that it "collapses runs of more than three bullets," which is a polite way of saying it deletes your list.
What structure-aware cleaning does differently
A structure-aware cleaner parses the text line by line first, then decides what to touch. It recognizes:
- Headings (
#through######) - Bullet lists (
-,*,+, and others) and their indentation - Numbered and lettered lists
- Blockquotes (
>) - Fenced code blocks and inline code
Inside those, it leaves spacing and punctuation alone. Outside them, it removes the noise: invisible characters, non-breaking spaces, em dashes, smart quotes, double spaces, and runaway blank lines.
The result
You get text that is clean and still shaped the way you wrote it. Your three-step numbered list is still three steps. Your code sample still has its indentation. Your headings still break up the page. Only the junk is gone.
This is exactly how textscrubr is built. It even preserves the zero-width joiners that real emoji need, so a 👩💻 stays whole instead of falling apart, while still removing the zero-width spaces that are pure noise.
When this matters most
- Publishing AI drafts to a blog or CMS, where the Markdown has to survive.
- Cleaning code comments or snippets, where one changed character breaks the build.
- Prepping structured documents, where collapsing the lists means rebuilding them by hand.
If your text has any structure worth keeping, reach for a cleaner that reads it before it scrubs it.