Twelve individually toggleable cleaning operations, six one-click presets, case transformation, and real-time stats — all running instantly in your browser.
Every operation has its own toggle so you control exactly what gets cleaned. Remove double spaces, line breaks, blank lines, tabs, HTML tags, smart quotes, Unicode symbols, invisible characters, non-ASCII, and more. Each toggle works independently — mix and match to build the exact cleaning pipeline you need.
Don't want to configure each toggle? Choose from six curated presets: General Clean for everyday use, PDF/Word Paste for fixing document copy-paste issues, HTML Strip for removing markup, Single Line for collapsing into one paragraph, ASCII Only for stripping all non-ASCII, and Minimal for a light touch.
As you type or paste, see exactly what was removed: extra spaces, line breaks, tabs, HTML tags, smart quotes, invisible characters, and total characters eliminated. A percentage reduction shows how much smaller the cleaned text is. Every stat updates live as you toggle options on and off.
Detect and strip characters you can't even see: zero-width spaces, zero-width joiners, byte order marks (BOM), soft hyphens, word joiners, and directional formatting characters. These invisible characters commonly sneak into text copied from websites, PDFs, and rich text editors, causing subtle bugs and display issues.
Convert text case as part of the cleaning pipeline: lowercase, UPPERCASE, Title Case, or Sentence case. Case transforms are applied after all other cleaning operations, so you get properly formatted output in a single pass. Useful for normalizing headings, names, or bulk-converting pasted content.
Remove all HTML markup from pasted content — <p>, <div>, <span>, <b>, <a> tags and more. Perfect for converting rich text or web page content to plain text. The tag counter shows exactly how many tags were removed. Combined with the smart quotes fixer, this handles most web-to-plain-text conversion needs.
Messy text is everywhere — PDFs, emails, web pages, documents. Our text cleaner handles them all.
Clean up text copied from PDFs, Google Docs, or Word that comes with random line breaks, double spaces, and smart quotes. Normalize formatting before pasting into a CMS, email, or publishing platform. Remove invisible characters that cause rendering bugs.
Strip HTML tags from scraped content, normalize line endings between Windows (CRLF) and Unix (LF), remove zero-width characters causing parsing errors, and sanitize user input strings. The ASCII-only mode is invaluable for cleaning data for systems that don't support Unicode.
Prepare text data for CSV imports, database entries, or analysis tools. Clean up exported spreadsheet data, remove non-printable characters that break parsers, normalize whitespace, and standardize case for consistent categorization and matching.
Clean text before pasting into email templates, forms, or social media platforms. Remove rich formatting that breaks plain-text emails, fix smart quotes that display as garbage characters in some email clients, and trim excess whitespace from newsletter drafts.
Paste or type text into the input area and the cleaner processes it instantly through a pipeline of up to 13 operations, each controlled by its own toggle. Operations run in a carefully ordered sequence — for example, HTML tags are stripped before spaces are normalized, and case transformation happens last. The cleaned result appears in the output panel in real time, along with stats showing exactly what was removed.
Smart quotes (also called curly quotes) are the typographically correct quotation marks used in published text: “ ” instead of " ". Word processors like Microsoft Word and Google Docs automatically convert straight quotes to smart quotes. While they look better in print, they can cause problems in code, CSV files, databases, command-line tools, and email clients that don't support Unicode. The cleaner also converts em dashes (—) to double hyphens and ellipses (…) to three dots.
Invisible characters are Unicode code points that produce no visible output but are present in the text data. Common examples include zero-width spaces (U+200B), byte order marks (U+FEFF), soft hyphens (U+00AD), zero-width joiners (U+200D), and directional formatting characters. They sneak into text from web pages, PDFs, word processors, and copy-paste operations. They can cause string comparisons to fail, break JSON parsing, interfere with regular expressions, and produce unexpected whitespace in rendered output.
This option strips any character outside the basic ASCII range (character codes 0–127). This includes accented characters (e.g., é, ü), emojis, CJK characters, mathematical symbols, and all other non-Latin characters. Use this when your target system only accepts ASCII, such as legacy databases, certain APIs, or systems that lack proper Unicode support. Note that this is an aggressive operation — only enable it when you specifically need ASCII-only output.
"Remove blank lines" collapses three or more consecutive newlines into two — so paragraph breaks are preserved but excessive whitespace between paragraphs is eliminated. "Remove all line breaks" is more aggressive: it replaces every newline with a space, merging all text into a single continuous paragraph. Use blank line removal for general cleanup; use full line break removal when you need single-line output (e.g., pasting into a spreadsheet cell or form field).
Different operating systems use different characters to represent line breaks. Windows uses CRLF (carriage return + line feed, \r\n), macOS and Linux use LF (\n), and old Mac systems used CR (\r). This option converts all line endings to the Unix standard LF format. This prevents issues when sharing text files between systems or when pasting text into tools that expect consistent line endings.
Absolutely — this is one of the most common use cases. Text copied from PDFs often contains random line breaks in the middle of sentences (because the PDF preserved visual line wrapping), extra spaces, non-breaking spaces that look like regular spaces but aren't, and various invisible characters. Use the "PDF / Word Paste" preset for best results — it removes line breaks, strips HTML, fixes invisible characters, and normalizes all spacing in one click.
The HTML stripper uses a regex pattern to match and remove anything between angle brackets (< and >). This handles standard tags like <p>, <div>, <span>, self-closing tags like <br/>, and tags with attributes. It does not decode HTML entities — & remains as & in the output. For basic web-to-plain-text conversion, combining HTML stripping with double space removal and blank line cleanup gives excellent results.
Yes to all three. The cleaner runs entirely in your browser — your text is never sent to any server. There are no accounts, no cookies, no tracking, and no limits on text length or usage. When you close the tab, everything is gone. Process sensitive documents, confidential emails, or private data with complete confidence that nothing leaves your device.
Every day, billions of text operations happen across the internet — copy-paste, import, export, convert, upload. And in a remarkable number of those operations, something goes wrong with the text formatting. A paragraph copied from a PDF arrives with line breaks in the middle of every sentence. An email draft pasted from Word contains invisible characters that break a database query. A web page's content, scraped for data processing, is littered with HTML tags and typographic characters that downstream systems cannot interpret. Text cleaning is the silent, essential step that makes digital text actually work.
The clipboard is the most used data transfer mechanism in computing, and it is also one of the most problematic. When you copy text from a rich source like a web page, PDF, or word processor, the clipboard captures not just the visible characters but also formatting metadata, invisible control characters, and layout information. When that text is pasted into a plain-text context — a form field, a code editor, a spreadsheet cell — the formatting is stripped but the artifacts remain: non-breaking spaces that behave differently from regular spaces, soft hyphens that appear in some contexts but not others, zero-width characters that are completely invisible but affect string operations.
PDFs are particularly notorious offenders. Because PDF is a visual layout format rather than a text flow format, the text stored in a PDF reflects how it looks on a printed page, not how it should flow as prose. Each visual line in the PDF is stored as a separate text segment, so copying a paragraph produces text with hard line breaks after every 60-80 characters. Sentences are chopped mid-word, hyphenated words carry their hyphens, and paragraph breaks become indistinguishable from line-within-paragraph breaks. A text cleaner that can rejoin these broken lines into proper paragraphs saves enormous manual editing effort.
Perhaps the most insidious text contamination comes from characters you literally cannot see. The Unicode standard defines dozens of control and formatting characters that produce no visible output but occupy space in the character stream. The zero-width space (U+200B) was designed for indicating possible line break points in languages without word separators, but it frequently appears in text copied from web pages where it was used for CSS styling or accessibility purposes. The byte order mark (U+FEFF) is supposed to appear only at the beginning of a file to indicate encoding, but it often leaks into the middle of text through careless string concatenation or encoding conversion.
These invisible characters cause real problems. They make two visually identical strings fail equality checks. They break JSON and XML parsers that encounter unexpected code points. They produce mysterious whitespace in rendered output. They cause database uniqueness constraints to fail on records that look identical to human eyes. A systematic invisible character scanner and remover is not a convenience — for developers and data professionals, it is a necessity.
Word processors convert straight quotation marks into typographically correct smart quotes because they look better in published documents. But smart quotes are Unicode characters — they exist outside the basic ASCII range. When smart-quoted text enters systems that expect ASCII — older email clients, CSV parsers, command-line tools, some APIs — the result is character encoding errors: the dreaded question marks, diamonds, or garbage characters that appear when a system encounters a code point it cannot interpret.
The same issue affects em dashes, en dashes, and ellipsis characters. Word processors automatically convert two hyphens into an em dash and three periods into an ellipsis character. These conversions improve typography but create compatibility problems in downstream systems. A good text cleaner converts these typographic characters back to their ASCII equivalents — straight quotes, regular hyphens, and three-dot sequences — ensuring maximum compatibility across all platforms and systems.
Copying text from web pages often brings along HTML markup, either visibly (raw tags in the text) or invisibly (formatting that affects behavior). Some email clients and rich text editors preserve HTML tags when you paste web content, resulting in visible angle-bracket markup mixed into your text. Even when tags are not visible, non-breaking spaces ( ), line breaks (<br>), and other HTML entities can persist in the pasted text, causing spacing anomalies and rendering issues.
Effective text cleaning requires operations to run in the correct order. Our cleaner applies operations in a carefully designed sequence: line ending normalization first (to ensure consistent newline handling), then HTML tag removal, then invisible character removal, then typographic character conversion, then whitespace normalization, and finally case transformation. This ordering ensures that each operation works on the cleanest possible input from the previous step, preventing interactions where one operation undoes or interferes with another.
The toggle-based approach gives you full control over this pipeline. Need to remove HTML tags but keep smart quotes? Just toggle HTML stripping on and smart quote conversion off. Want to convert case without changing whitespace? Enable only the case transform. Every combination of toggles is valid and produces predictable, consistent results because the underlying pipeline handles operation ordering automatically.