Text Inspector
Count words, characters, sentences and lines, with an estimated reading time.
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Count words, characters, sentences and lines, with an estimated reading time.
Count words, unique words, sentences, paragraphs, and estimated reading time.
Add sequential numbers to each line while optionally preserving blank lines.
Reverse Unicode text character by character without corrupting multibyte text.
Reverse the order of words while keeping each word intact.
Count sentence-like units using bounded punctuation-aware segmentation.
Count paragraphs separated by one or more blank lines.
Normalize spaces, tabs and line breaks while optionally preserving paragraphs.
Normalize hashtag text, remove duplicates and format inline or by line.
Check AA and AAA contrast thresholds for normal and large text.
Generate a copy-ready Code 39 barcode as standards-based SVG for supported uppercase text.
Generate a correctly escaped Markdown link with optional title text.
Measure characters with and without whitespace, letters, digits, and lines.
Convert text to uppercase, lowercase, title case, sentence case, or toggled case.
Normalize line endings, repeated spaces, blank lines, and optional HTML markup.
Remove repeated lines while preserving the first occurrence and original order.
Sort text lines alphabetically, naturally, or by length in either direction.
Encode UTF-8 text to Base64 or strictly decode Base64 back to text.
Generate SHA-2, SHA-3, SHA-1, MD5, or HMAC digests from text.
Replace literal text with optional case-sensitive matching.
Add a controlled prefix and suffix to every selected line.
Join lines using a chosen separator while normalizing surrounding whitespace.
Wrap paragraphs to a selected character width for email, terminals or plain-text files.
Shorten text to a maximum length with a safe suffix and whole-word option.
Extract valid-looking email addresses from pasted text and optionally remove duplicates.
Extract HTTP and HTTPS URLs while removing common trailing punctuation.
Extract signed integers and decimal values from mixed text.
Extract Unicode hashtags from social captions and campaign copy.
Extract social @mentions from captions, comments and outreach text.
Extract words and sort them alphabetically with optional deduplication.
Randomize line order for fair draws, exercises and content variation.
Rank words by occurrence and percentage share.
Measure exact phrase occurrences as a percentage of total words.
Generate one- to five-word phrases for language and SEO analysis.
Encode UTF-8 bytes as eight-bit binary groups or decode them back to text.
Compare two texts line by line and classify additions, removals and changes.
Create an acronym from the first character of each meaningful word.
Remove Unicode punctuation and symbols using a chosen replacement.
Count each punctuation and symbol character in the supplied text.
Extract text enclosed in straight or typographic quotation marks.
Extract simple text enclosed in parentheses, brackets or braces.
Sort detected sentences alphabetically in ascending or descending order.
Randomize detected sentence order for exercises and content variations.
Convert text to sentence case after normalizing letter case.
Apply Unicode title case with optional lowercasing of common connecting words.
Create an ASCII-oriented URL slug when transliteration support is available.
Check whether normalized letters and numbers read the same in both directions.
Compare two normalized strings to determine whether they contain the same characters.
Encode text using RFC 4648-style Base32.
Decode valid Base32 text into its original bytes.
Create a text data URI with Base64 or percent encoding.
Estimate reading time from word count and a selectable reading speed.
Encode text bytes using the Bitcoin-style Base58 alphabet.
Estimate speaking time from word count and presentation speed.
Decode Bitcoin-style Base58 text into bytes.
Measure unique-word share using the type-token ratio.
Calculate average Unicode character length across detected words.
Decode HTML5 entities back into Unicode text.
Calculate average words per detected sentence.
Remove a bounded built-in list of common English, Urdu or Arabic stop words.
Try a shorter keyword or choose another category.
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