Get LLM output ready for an originality scan
Plagiarism and AI-detection tools work on plain prose. Paste raw LLM output into them and the markdown headings, bullet symbols, code fences, and repeated boilerplate can throw off the comparison. This tool strips all of that away and removes duplicate sentences, leaving the clean text a scanner actually wants — so your similarity score reflects the writing, not the formatting.
Why formatting disrupts plagiarism scanning
Originality detectors typically tokenize text into sentences or short passages, then compare those against a reference corpus. When markdown symbols are present, the tokenizer may misread sentence boundaries, split a single sentence into fragments, or skip content inside code fences entirely. Common problems include:
- Heading hashes (
##,###) appearing as sentence-initial characters, causing the passage to fail matching against clean-prose versions of the same text in the corpus. - Code blocks inflating or deflating the similarity score depending on whether the scanner indexes code. If your content is prose-plus-code and the scanner ignores fences, the code is just noise.
- Duplicate boilerplate — common LLM conclusions like “In summary, the main points are…” — appearing multiple times and registering as repeated self-plagiarism within the document.
- Bullet markers (
-,*) attaching to word tokens and preventing phrase matching.
Cleaning before scanning ensures the score reflects the actual prose content of the text.
How it works
The cleaner runs a sequence of passes. It removes markdown syntax — heading hashes, bold and italic markers, link wrappers (keeping the visible text), inline code backticks, and fenced code blocks. It collapses runs of whitespace and blank lines into normal spacing. Then it splits the text into sentences and removes exact duplicates, keeping the first occurrence of each, which catches the restated conclusions that long LLM responses tend to produce. The result is a single clean block of prose with a word and character count so you know what the scanner will receive.
What cleaning removes and what it keeps
| Input element | What the cleaner does |
|---|---|
## Heading text | Becomes Heading text (hashes stripped) |
**bold** or _italic_ | Becomes plain text |
`inline code` | Becomes plain text |
```code block``` | Removed entirely |
[link text](url) | Becomes link text |
| Duplicate sentences | Second and subsequent copies removed |
| Paragraph line breaks | Collapsed to single spaces |
Tips and notes
Run this just before pasting into your plagiarism or originality detector for the cleanest comparison. Because the tool only strips formatting and verbatim repeats, it never alters your actual wording — what comes out is the model’s prose without the markup. Everything runs locally, so it is safe for confidential drafts. If you need to keep structure for a different purpose, keep the original and use this cleaned copy only for the scan. Remember that no automated detector is definitive; treat its score as one signal among several.