Readability & Word Count Analyzer

A word counter turns a draft into measurable editorial signals without confusing length with quality. This tool counts words, characters, sentences, and paragraphs, then estimates reading and speaking duration. It also highlights long sentences and repeated keywords. Use those signals to identify passages worth reviewing, not to force every article into the same formula. The calculations run locally, so ordinary pasted drafts do not need to travel to a remote analysis service.

How to use it

1. Replace the sample in Your text with the passage you want to review.
2. Check words, characters, and characters without spaces against your publishing requirements.
3. Compare reading time and speaking time with the format you are preparing.
4. Review Flesch ease, grade level, and the plain-English interpretation together.
5. Read the three longest sentences aloud, then inspect the keyword table for unnecessary repetition.

Understanding the output

Words are sequences of Unicode letters or numbers, with internal apostrophes supported. This is practical for English editorial copy but is not a language-aware tokenizer for every writing system. Character count uses JavaScript string length, so certain emoji and combined characters can occupy more than one code unit. Without spaces removes whitespace, including tabs and line breaks. Paragraphs are blocks separated by blank lines rather than every visual line.

Reading duration assumes 238 words per minute. Speaking duration assumes 150 words per minute. Both are planning estimates: unfamiliar material, dramatic pauses, slide changes, and accessibility needs change real timing. Average sentence length divides total words by detected sentences. Sentence boundaries use punctuation, so abbreviations, initials, and decimal numbers can affect the result.

Readability is a diagnostic, not a verdict

Flesch Reading Ease combines sentence length with estimated syllables per word. Higher values generally indicate easier English prose. Flesch-Kincaid grade expresses a related estimate on a US school-grade scale. The syllable counter uses spelling patterns rather than a pronunciation dictionary, so brand names, technical terms, and unusual endings can produce imperfect estimates. Very short samples can generate extreme scores, including negative grades.

Pro tips

• Analyze the main article separately from menus, footers, and legal boilerplate.
• Split a long sentence when it contains two distinct claims, not merely because a score looks low.
• Keep necessary specialist terms and explain them with examples.
• Use the keyword table to spot repetition, not to target a supposedly ideal SEO density.

Keyword density divides each displayed keyword count by all detected words, including stopwords. Common English stopwords are excluded from the ranked list, but they still contribute to the denominator. Case is normalized, while different inflections remain separate words. A term occurring twice in a four-word passage therefore has a density of 50 percent.

Common editorial use cases

Estimate narration length before recording, check an introduction against a brief, or compare two revisions of a landing page. Readability scores cannot detect factual errors, weak arguments, or a mismatch with reader intent. A useful final pass combines these metrics with human editing and a clear understanding of the audience.

Further reading and practical checks

Read Word counter and readability analysis: practical background for a broader workflow, and use the related json formatter tool when the next task requires it. The official reference provides additional technical context. Keep those references alongside your own acceptance criteria so a convenient result does not become an undocumented assumption.

Before handing off work, compare one known example against a manually verified expectation. Save the original input, identify the settings that matter, and explain any approximation to the next person. Small checks catch unit mistakes, formatting differences, and misplaced confidence early. When requirements change, repeat the same example before applying the workflow to a larger collection.

Keep context with the result

A copied result is easier to reuse when its source and purpose are clear. Include a short note describing where the input came from, which part of the output matters, and what you expect a teammate to verify. Avoid sharing sensitive source material unnecessarily. When a result seems surprising, reduce the example to the smallest input that reproduces it, then compare that case against the documented rules. This turns an ambiguous discrepancy into a concrete question that is much easier to investigate.