Word counter and reading time
Measure words, characters, sentences, paragraphs, unique terms and estimated reading time. Use it for articles, essays, briefs and captions.
TEXT TOOL COLLECTION
These focused tools cover the common steps between a rough draft or copied list and a result that is ready to review. Text stays in the current browser session.
Measure words, characters, sentences, paragraphs, unique terms and estimated reading time. Use it for articles, essays, briefs and captions.
Check titles, descriptions, interface labels and form values where a character limit matters more than a word target.
Collapse uneven empty rows while keeping readable paragraph breaks in copied notes, emails and exported text.
Keep the first occurrence of each non-empty line. Preserve a copy of the original whenever repeated rows may represent real quantities.
Alphabetise names, tags and values, use natural number order, or reverse the result. Sorting after cleanup makes duplicate review easier.
Find added, removed and unchanged lines between two drafts. Use a full code-diff tool when exact positions and character-level changes matter.
Change English text to uppercase, lowercase, title case or sentence case, then review proper names and acronyms manually.
Rank repeated terms with counts and percentages to support editing and vocabulary review.
Pull unique address-like values or web links from unstructured text for manual review.
Replace exact text or a reviewed regular-expression pattern throughout a draft.
Normalise pasted spacing or strip common numbered-list prefixes without flattening the document.
Remove scripts, styles and markup while keeping readable block and line breaks.
Move between one-item-per-line lists and simple custom-delimited text.
Pull signed integers, decimals and grouped values from mixed text for review.
Wrap every line with repeated syntax for quoted lists, identifiers and simple code fragments.
Change character or list order for testing, review and low-stakes randomisation.
Keep the first case-insensitive occurrence when building a compact vocabulary or cleaning tags.
Create deduplicated candidate lists from unstructured text, then verify them against the source.
Keep the original, normalise whitespace, remove empty rows, decide whether duplicates are meaningful, sort only if order is not important, and compare the result before sharing. The complete list-cleaning guide explains this sequence.
No. These tools perform their main transformations in the browser.
The pages do not keep server-side history. Preserve the original input or copy the result into a new document before continuing.