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Prompt Utilities

Character Counter

How long is this text — for a human and for the platform it has to fit? Paste it to count characters, words, lines, and reading time, and see at a glance whether it busts Twitter's 280, fits a 160-character meta description, or runs long for a talk. It measures length in the units people read; for tokens and cost, that's the Token Counter. Runs entirely in your browser — your text is never sent anywhere.

Paste any text — a post, a description, an essay, a script. Nothing leaves your browser; the report shows counts only, never your text.

Reading Pace

Sets the reading-time estimate; speaking time uses a steady ~130 wpm.

Length Analysis (live — metrics & limits, not the report)

                

AI Resource Library

Resources for this tool

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Prompt Engineering

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.

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Prompt Engineering

Word Counter

Count words in any text, with sentence and paragraph structure and reading time — for essays, articles, and anything with a word target.

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How it works

Paste any text and pick a reading pace (slow, average, or fast). The Text Metrics Engine counts it deterministically: characters with and without spaces, words, lines, paragraphs, and sentences, plus a Density read-out of average word length and average sentence length. The Reading Time Engine estimates how long the text takes to read at your chosen pace and to speak aloud at a steady pace. The Platform Limits Engine checks the character length against common caps — X/Twitter, SMS, meta description, Google title, Instagram, LinkedIn — and shows whether it fits, with the exact characters left or the amount over. Click Measure Text for the full report: Character Metrics, Word Metrics, Reading Metrics, Text Structure, Platform Notes, and honesty notes on how counts work. Everything runs in your browser; the report shows counts only and never echoes your text. Counts are in text units a human reads — for model tokens and cost, the report points you to the Token Counter.

Use cases

  • Counting characters, words, and lines in any text
  • Checking a post or description against platform length limits
  • Estimating reading time and speaking time
  • Sizing copy to a character or word target

Pro tips

  • Watch the Platform Notes panel. The number that matters when you are over a limit is the amount over — it tells you exactly how many characters to cut, not just that you missed.
  • Pick the right reading pace. Technical or dense material reads slower than casual prose, so set the pace to match before trusting the reading-time estimate.
  • Speaking time runs slower than reading time. If you are writing a talk or voiceover, size to speaking time — presenters who write to a reading estimate always run over.
  • Use characters-without-spaces for fields that count it that way, and remember some emoji and combined scripts can count as more than one character in a text field.

FAQ

How is this different from the Token Counter?

Different units for different audiences. The Character Counter measures text units a human reads and a platform limits — characters, words, lines, reading time. The Token Counter measures model units — tokens, the sub-word chunks a model processes and bills — and prices them. A 280-character tweet and its token count are different numbers: count characters here when the limit is a platform or a reader, and count tokens there when the limit is a model's context or an API bill.

How is this different from the Context Window Estimator?

The Context Window Estimator answers "will it fit a model's context window?" — a fit verdict measured in tokens. This tool never touches a model window; it answers "how long is this for a person or a platform?" in characters and words. One is about a model's capacity; the other is about human and platform limits.

How accurate is the reading and speaking time?

They are estimates from word count divided by a reading or speaking pace — the same math behind a "5 min read" badge. Real pace varies by reader, speaker, and material: a technical paper reads slower than a casual post, and a careful presenter speaks slower than a fast one. The reading pace is selectable for exactly this reason; treat the result as a solid estimate, not a stopwatch.

How are characters counted — what about emoji?

Characters are counted as the units a text field counts (UTF-16 code units), which is what most platforms and textareas enforce. Some emoji and combined scripts can count as more than one unit in that scheme, which is noted in the report. If a specific platform counts differently — Twitter, for instance, weights some characters — treat this as a close, honest estimate rather than that platform's exact internal count.

Are the platform limits exact and current?

They are the common, well-known caps — Twitter 280, SMS 160, meta description ~160, and so on — offered as context so you can size text without leaving the page. Platforms occasionally change limits and apply their own counting rules, so confirm against the platform itself when a few characters decide it. The goal is fast orientation, not a guarantee.

Why does multilingual text count differently?

Because languages are built differently. Word and sentence boundaries vary — some scripts do not separate words with spaces — and CJK characters pack more meaning per character, so a translated sentence can have a very different character and word count from its English source. The tool counts honestly and notes that language affects every metric; it does not pretend one ruler fits all scripts.

Is my text sent anywhere?

No. The whole tool runs in your browser with deterministic counting — no AI, no server round-trip. Your text never leaves the page, and the report deliberately shows counts only, never echoing your content back. Copy or download the report yourself.