Free Tool

Readability checker with six algorithms.

Paste your text and see Flesch Reading Ease, Flesch-Kincaid grade, Gunning Fog, SMOG, Coleman-Liau, and ARI scores update live. No signup, runs in your browser.

Overall reading level
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Flesch Reading Ease
Flesch-Kincaid Grade
Gunning Fog
SMOG Index
Coleman-Liau
ARI
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Complex words (3+ syl)
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Health writers, technical communicators, journalists, and bloggers all need to know if their text is too dense for the audience. This checker runs all six standard readability algorithms at once (Flesch Reading Ease, Flesch-Kincaid, Gunning Fog, SMOG, Coleman-Liau, and ARI) and gives you an averaged grade level and reading age.

What each algorithm tells you

Six different formulas, six slightly different answers. Each was developed for a different audience or use case, and they disagree on purpose. Looking at all of them together is more honest than picking one.

Flesch Reading Ease

The classic, developed by Rudolf Flesch in 1948. The only score where higher means easier (others output a grade level). 100 = trivially easy, 0 = academic dissertation. Aim for 60+ for general audiences.

Flesch-Kincaid Grade Level

The same inputs as Flesch Reading Ease, recast as a US school grade. Commissioned by the US Navy in 1975 to grade technical manuals. Microsoft Word's built-in score uses this. Most widely cited in publishing.

Gunning Fog Index

Developed by Robert Gunning in 1952. Counts "complex" words (3+ syllables) instead of average syllable length. Outputs years of formal education needed to read fluently. Standard prose lands around 8.

SMOG Index

"Simple Measure of Gobbledygook" by G. Harry McLaughlin (1969). Designed for healthcare and government materials where comprehension is critical. Most accurate on samples of 30+ sentences. Now the standard in medical writing.

Coleman-Liau Index

Built by Coleman and Liau (1975) for digital text. Uses character counts instead of syllables, which avoids the error introduced by syllable-counting heuristics. Often more consistent than Flesch-Kincaid on machine-generated or unusual text.

Automated Readability Index (ARI)

Also character-based. Developed by Smith and Senter (1967) for the US Air Force to grade printed materials. Standard in US government documents.

How to use the scores

Don't optimize for a single score. Write naturally first, then check. If multiple scores cluster around grade 12+ but your audience is general readers, the prose is too dense. Common fixes that lower readability score (make it easier):

  • Shorter sentences (avg 14–18 words is the sweet spot for general prose)
  • More common words (replace polysyllabic Latinate words with shorter Anglo-Saxon equivalents where possible)
  • Active voice (cuts word count and syllables both)
  • Break long paragraphs (paragraphs don't affect the math directly, but shorter ones encourage shorter sentences)

Conversely, if you're writing literary fiction or technical prose for an expert audience, a "high" score (grade 12+) may be exactly right.

Reading levels by content type

ContentTypical Flesch-Kincaid gradeReading age
Children's picture books1–36–8
Middle grade fiction4–69–11
YA novels5–710–12
News articles (general press)6–911–14
Adult commercial fiction5–910–14
General-audience blog posts7–912–14
Business / trade publications10–1215–17
Adult literary fiction8–14 (varies wildly)13–19
Academic / scientific papers14–1819–23

Beyond a single check

Readability is one snapshot. The deeper question (does your writing match your audience consistently across an entire manuscript or a year of blog posts) needs longer data. Authorlytica tracks the writing itself rather than the readability of any single passage, but the two work together: readability tells you whether what you wrote today will land, the tracker tells you whether you wrote today at all.

Read next

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Authorlytica tracks the daily count, streak, and pace, the long view that no single readability check can show. Free forever plan, no card.

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