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HomeWeb / FrontendReadability Checker

About Readability Checker

Readability Checker preview - Web / Frontend tool

Check content readability with Flesch-Kincaid and other readability scores. Part of the DevTools Surf developer suite. Browse more tools in the Web / Frontend collection.

Use Cases

  • Check marketing copy readability before publication to maximize audience comprehension.
  • Audit technical documentation for sections that are unusually dense for the target reader level.
  • Screen customer support email templates to ensure agents can read and comprehend them quickly.
  • Improve blog posts for SEO — search engines use engagement signals (time on page, bounce rate) that correlate with readability.

Tips

  • Target Flesch-Kincaid Grade Level 8–10 for general audience content — this matches the average adult reading level in the US.
  • Sentences over 25 words are the primary driver of poor readability scores — break them before adjusting vocabulary.
  • Technical content legitimately scores lower (grade 12+) — filter for your specific audience rather than optimizing for the lowest possible score.

Fun Facts

  • The Flesch Reading Ease formula was developed by Rudolf Flesch in 1948 and was adopted by the US Navy to improve the readability of its training manuals.
  • The average US adult reads at an 8th grade level according to the National Center for Education Statistics, though this varies significantly by demographic and subject matter.
  • Plain language legislation (the Plain Writing Act of 2010) requires US federal agencies to write all public-facing documents at a level comprehensible by the average citizen.

FAQ

What's a good Flesch Reading Ease score?
60–70 is considered standard (plain English). 70–80 is fairly easy (common for consumer content). Below 30 is very difficult (academic journals). Most web content should target 60–70.
Which readability formula is most accurate?
No single formula is universally accurate — each weights sentence length and syllable/word count differently. Flesch-Kincaid is most widely used; Gunning Fog and SMOG are common alternatives. Use multiple metrics and treat scores as directional.

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