Readability Score Checker — Measure and Improve Your Writing

Readability scores measure how easy text is to read. They were originally developed to match textbooks to appropriate grade levels, but they're now widely used to assess web content, legal documents, marketing copy, and technical writing. Most readability formulas use two variables: sentence length and word complexity.

The major readability formulas

Flesch Reading Ease

The most widely used readability formula, developed by Rudolf Flesch in 1948:

score = 206.835 − (1.015 × avg sentence length) − (84.6 × avg syllables per word)

Scores range from 0 to 100 (higher = easier):

Plain English guidelines target a score of 60–70 for most business writing. US government plain language guidelines recommend a score above 60.

Flesch-Kincaid Grade Level

Same variables as Flesch Reading Ease, but outputs a US school grade level instead of a 0–100 score:

grade = (0.39 × avg sentence length) + (11.8 × avg syllables per word) − 15.59

A grade of 8.0 means the text is appropriate for an 8th grader. This formula is used by Microsoft Word's readability statistics and the US Department of Defense for its documents.

Gunning Fog Index

Developed by Robert Gunning in 1952:

fog = 0.4 × (avg sentence length + percentage of complex words)

"Complex words" are words with three or more syllables. The output is a grade level. Fog scores above 17 indicate text that is virtually impossible to read. Newspapers typically target a Fog score of 8–12.

SMOG Index (Simple Measure of Gobbledygook)

Specifically designed for health communication materials:

smog = 3 + √(count of polysyllabic words in 30 sentences)

SMOG is considered the most accurate predictor of reading comprehension difficulty for health-related text. The formula was designed to be calculated by hand, which is why it uses a simple square root rather than a weighted formula.

Coleman-Liau Index

Unlike other formulas, Coleman-Liau uses characters per word instead of syllables:

CLI = (0.0588 × avg letters per 100 words) − (0.296 × avg sentences per 100 words) − 15.8

This makes it fast to compute without syllable counting. It was developed for use with computer text analysis, before accurate syllable counting algorithms were common.

Automated Readability Index (ARI)

Also uses characters rather than syllables:

ARI = (4.71 × avg chars per word) + (0.5 × avg words per sentence) − 21.43

ARI was developed by the US Air Force for real-time readability assessment of technical manuals.

How syllables are counted

Syllable counting is the hard part of readability analysis. There is no simple rule — English spelling does not reliably indicate pronunciation.

A practical approximation:

1. Convert word to lowercase, strip non-alphabetic characters
2. Count consecutive vowel clusters ([aeiouy]{1,2})
3. Subtract 1 if word ends in silent e
4. Subtract 1 for common suffixes like -ed, -es, -ing that don't add syllables
5. Ensure minimum count of 1

function countSyllables(word) {
  word = word.toLowerCase().replace(/[^a-z]/g, '')
  if (!word) return 0
  if (word.length <= 3) return 1
  word = word.replace(/(?:[^laeiouy]es|ed|[^laeiouy]e)$/, '')
  word = word.replace(/^y/, '')
  const matches = word.match(/[aeiouy]{1,2}/g)
  return matches ? matches.length : 1
}

This approach is ~85–90% accurate for common English words. The remaining errors (especially for technical terms, proper nouns, and loanwords) are small enough to not meaningfully change the final readability score.

What affects readability scores

Sentence length

The single biggest factor in most readability formulas. Sentences over 25 words push scores toward "difficult" in almost all formulas. Breaking one long sentence into two shorter ones often improves Flesch by 5–10 points.

Word complexity

Long words (3+ syllables) are penalized by Gunning Fog and SMOG. This creates an incentive to prefer simpler synonyms: "use" instead of "utilize", "start" instead of "initiate", "help" instead of "facilitate".

Passive vs active voice

Readability formulas don't directly measure passive voice, but passive constructions tend to be longer ("The report was reviewed by the committee" vs "The committee reviewed the report"), which increases sentence length scores indirectly.

Technical vocabulary

Technical terms are often polysyllabic (authentication, infrastructure, configuration). This means technical documentation will naturally score as "difficult" even when it's appropriately written for its audience. Readability scores are most useful for general audience content, not domain-specific technical writing.

Appropriate reading levels by content type

Reading level is not quality — academic papers are supposed to be complex. The goal is appropriate complexity for your audience, not the lowest possible score.

How to check readability for free

1. Go to Readability Score Checker
2. Paste or type your text — scores update automatically as you type
3. Review all six formulas and the overall grade band
4. Check the improvement suggestions panel for specific actions
5. Look at the statistics: sentence count, word count, complex word percentage
6. Use the top words list to identify overused vocabulary

Scores are computed entirely in your browser — text is never sent to a server.