Free Readability Checker See What Your Sentences Actually Score
This tool applies six established readability formulas to the same passage in one pass: Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog, SMOG, Coleman-Liau and the Automated Readability Index. Paste an abstract, an essay or an article and get a grade-level reading benchmarked against targets built specifically for academic and general-audience documents. A single formula can mislead; six of them agreeing on the same range rarely does.
Scores your text with six readability formulas at once: Flesch, Flesch-Kincaid, Gunning Fog, SMOG, Coleman-Liau and ARI.
0 / 1,000 words
84,000+
International Researchers
Average Rating
Trusted by researchers publishing in
How to check your readability score in three steps
Add your passage
An abstract, a full chapter, a lay summary or a cover letter, up to 1,000 words. However long the excerpt, every score computes together in one pass.
Compare all six numbers
Treat the average as the headline figure. The individual formulas beneath it show whether the difficulty comes from sentence length, word length, or both together.
Cut until you land in the band
Break the long sentences, swap noun phrases for verbs, and watch the numbers move as you edit until the passage sits where your reader needs it.
A readability checker built for serious writing
All six numbers side by side
Flesch, Flesch-Kincaid, Fog, SMOG, Coleman-Liau and ARI computed together, so an outlier from one formula never sends a revision the wrong way.
Targets built for real documents
Separate bands for research prose (13-16), general-audience writing (8-12) and participant-facing documents (6-8), rather than one blanket rule for every kind of text.
Sentence and syllable counts shown
Average sentence length, syllables per word and the share of complex words are broken out, so you can see which lever actually moves the number.
Nothing sent to a server
Every formula runs in the browser tab you already have open. An unpublished chapter never has to leave the machine it was written on.
What a readability formula can and cannot tell you
A readability formula estimates the schooling a reader would need to follow a passage on a single pass. It has no opinion on whether the argument holds, only on two habits that wear a reader down: sentences that run long, and stretches of multi-syllable words with no shorter option offered instead. Studies of published journals put ordinary articles around grade 14 to 16, with medical abstracts drifting toward 18, and multi-decade surveys of scientific writing show the prose has been climbing in difficulty for years, even as editors ask for the opposite.
The consequence is not abstract. A reviewer forms an impression from the abstract before reaching the introduction, and a paragraph that takes two readings to parse works against the paper regardless of the result described inside it. Readers outside your subfield, including reviewers assigned partly for breadth, decide from that same paragraph whether the work is worth following further. Meanwhile the paperwork around a study answers to its own rules: participant materials at grade 6 to 8, funding summaries in plain language, a press release anyone should be able to read. One project can easily need all three bands inside a single week, which is why this page checks six formulas rather than settling on one.
Machine-drafted prose adds a wrinkle worth watching for. A chatbot's default output tends to hold one difficulty band from the opening line to the last, missing the give and take a person's writing shows naturally between a short setup sentence and a longer one unpacking it. Running a passage section by section instead of end to end usually surfaces the stretch nobody actually revised. Pair the count here with the burstiness checker for rhythm, and bring in the TextPulse humanizer once the fix needed is a rewrite rather than a diagnosis.
Every formula reads the same draft a little differently
None of the six was built with your particular reader in mind, which is exactly the case for running all of them together.
Flesch Reading Ease
1948The earliest of the six and still the one most software reports by default. It weighs average words per sentence against average syllables per word on a 0-100 scale, where a higher reading runs easier. Most published research sits under 30 on this scale, so a paper reaching 30 to 50 stands out as unusually approachable.
Flesch-Kincaid Grade
1975A 1975 conversion of the Flesch formula into a US school-grade number, which is why it became the default citation in readability research. Surveys of published journals place medical abstracts near grade 18 and typical discussion sections around 16.
Gunning Fog Index
1952Weighs sentence length against the share of three-syllable-plus words, which makes it the formula quickest to react to jargon. When a Fog score runs well ahead of the Flesch-Kincaid grade for the same passage, vocabulary is doing more damage than sentence structure.
SMOG Index
1969Samples polysyllabic words across thirty sentences to gauge whether a reader will fully grasp the passage. It is the formula health communication relies on: consent forms and patient materials are typically required at grade 6 to 8, checked specifically with SMOG.
Coleman-Liau Index
1975Swaps syllable counting for characters per word, which machines can tally without ambiguity. Where it agrees with Flesch-Kincaid, trust the grade; where the two pull apart, the words in the passage are unusually long or short relative to how the sentences are built.
Automated Readability Index
1967Built from characters per word and words per sentence for military technical manuals, so it answers to long sentences more sharply than the others. That sensitivity makes it a fast early warning for a methods paragraph that has chained five steps into one fifty-word sentence.
Matching the target band to the document
Fit the number to the reader, never the reverse. A single research project commonly needs three of these bands running at once.
One finding, two very different sentences
Both passages are scored live by this tool. The underlying claim never moved; only the sentence construction did.
"The utilization of a multifactorial analytical approach for the assessment of intervention efficacy across heterogeneous participant subgroups necessitated the implementation of a stratified statistical methodology capable of accommodating substantial variance in baseline demographic characteristics."
One 34-word sentence, four nominalizations, thirteen complex words.
"This analysis needed a statistical method suited to mixed groups. Baseline traits varied widely between participants. The method had to account for that variation."
Three short sentences, plain verbs in place of noun phrases, nothing lost.
Who uses the readability checker
Undergraduates and coursework writers
Check an essay against the band an instructor expects, and see which sentences are driving the difficulty up.
Graduate researchers
Pull an abstract or a discussion section back from the high twenties before a reviewer ever opens it.
Clinical and health researchers
Hold consent forms and participant materials at the grade 6-8 line most ethics committees set, checked specifically with the SMOG count.
Content and SEO writers
Web readers abandon dense paragraphs fast. Keep landing pages and articles inside a band a general audience will actually finish.
The numbers say grade 19.
Cutting sentence length takes an actual rewrite.
The TextPulse humanizer breaks up overloaded sentences, trades noun phrases for verbs and varies flat rhythm throughout a full draft, with every change tracked for approval, so the writing lands at the grade your reader expects without dropping a claim.