Character Counter
Paste any text and see characters, words, lines, and reading time at once — plus whether it fits Twitter, SMS, and meta-description limits.
Count words in any text, with sentence and paragraph structure and reading time — for essays, articles, and anything with a word target.
Word count is the unit most writing is measured in — assignments, articles, abstracts, posts — but a bare number misses the shape. This loads an essay-length text and reports words alongside the structure that gives them meaning: sentences, paragraphs, average sentence length, and how long the piece takes to read. When you have a word target to hit, the count is the headline and the structure tells you whether you got there with three long sentences or thirty short ones.
Paste the piece
An essay, article, or draft with a word target to hit.
Read the count and shape
Words alongside sentences, paragraphs, and average sentence length.
Hit the target
See whether the count came from long sentences or short ones.
The WORD METRICS and READING METRICS lead the report. This essay-length sample shows 'Words: 396' with 'Reading time (Average (~200 wpm)): 1 min 59 sec', so a word target and the time a reader spends both appear at once. Average sentence length beside the count tells you whether you hit the number with long sentences or short ones.
Yes — the count comes with the shape that gives it meaning. The report pairs 'Words: 396' with 'Sentences: 18', 'Paragraphs: 6', and 'Average sentence length: 22.0 words', so a bare number becomes a read on structure. That is the difference between hitting a word target with three long sentences versus thirty short ones.
Paste any text and see characters, words, lines, and reading time at once — plus whether it fits Twitter, SMS, and meta-description limits.
How long will this take to read? Estimate reading time from word count at a pace you choose — the "5 min read" label, calculated.
A character is what you type; a token is what a model reads. This shows when to count which, from the character side.
Know how many tokens a job will consume before you send it — input plus an assumed response, costed per call and at scale.
Token budget planning for real workloads: how much of the window a transcript actually consumes, what is left for the answer, and how much headroom remains.
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
Count characters, words, lines, and reading time — with live platform-limit checks for Twitter, SMS, meta descriptions, and more.