Flesch-Kincaid & SMOG Readability Scorer

What readability scores measure

Readability formulas are a family of statistical tools that estimate how difficult a piece of text is to read by counting features like sentence length and word complexity. They do not measure the quality of your argument or the accuracy of your claims, but they do give you a reliable proxy for the reading effort your audience is likely to need, which is why they are widely used in education, government, and content marketing.

What the formulas share

Readability formulas estimate how difficult a piece of text is to read by analysing sentence length and word complexity.¹ The Flesch Reading Ease formula came first, and the Flesch–Kincaid Grade Level formula followed later for U.S. Navy training materials.² Both tests reduce a passage to three countable features (words, sentences, and syllables) and then combine those counts with different weighting factors. Because they count the same core features, the two Flesch-based scores correlate closely even though their scales move in opposite directions.

What the formulas cannot capture

None of the formulas measure whether an argument is clear, well-structured, or accurate. They only count syllables, words, and sentences, and they do not account for every difference between readers or the effect of content, layout, and retrieval aids.³ A paragraph packed with short, familiar words scores well even when its logic is impenetrable, while a tightly reasoned argument full of technical terms can score poorly. Think of the scores as a proxy for reading effort, not a measure of quality.

Flesch-Kincaid Grade Level and Reading Ease

Both Flesch-Kincaid formulas use the same three inputs: word count, sentence count, and syllable count. Grade Level maps the result to a US school year, so a score of 8.0 suggests a text is readable by a typical eighth-grader. Reading Ease uses a 100-point scale where higher numbers mean easier reading. Microsoft recommends 60 to 70 for most standard files, while Grade Level is recommended around 7.0 to 8.0 for most documents.² The two scales are not directly convertible because they weight sentence length and syllable count differently.

For most general-audience web content, including blog posts, product pages, and documentation introductions, a Grade Level around 7 to 8 and a Reading Ease of 60 to 70 is a practical target. Specialist writing can sit higher when the audience expects domain vocabulary, but the score is a guide rather than a rule. Aiming for plain language without dumbing your content down is the balance most editors settle on.

A short example shows the arithmetic in action. The pangram The quick brown fox jumps over the lazy dog. has 9 words, 1 sentence, and 11 syllables, which works out to a Flesch Reading Ease of 94.3 and a Flesch-Kincaid Grade Level of 2.3. Both scores land far above the 60 to 70 target range for typical web content, which makes sense: short, familiar one-syllable words are exactly what the formulas reward.

SMOG Grade explained

SMOG (Simple Measure of Gobbledygook) was developed by G. Harry McLaughlin and published in 1969 as an alternative to formulas such as Gunning Fog.⁴ It focuses on polysyllabic words, those with three or more syllables, and it is widely used for checking health messages.⁵ The full formula counts polysyllabic words across three 10-sentence samples, takes the square root of the nearest perfect square, and adds 3 to produce a grade estimate.

SMOG is designed around three 10-sentence samples, so very short inputs are less stable than longer samples.⁵ That is why the tool shows "Need more text" for very short inputs. Because SMOG weights polysyllabic words more heavily than Flesch-Kincaid does, it can produce different grade estimates from the same passage. You should treat early scores on brief drafts as provisional rather than final.

How sentence highlighting works

The sentence-highlighting view annotates your text one sentence at a time so you can see exactly which passages are pushing your readability scores upward. Long sentences raise the average words-per-sentence input that every major formula relies on, so flagging them visually turns an abstract number into a concrete list of revision targets you can work through in order.

What gets flagged and why

The "View Highlights" view annotates your text sentence by sentence. Any sentence with 25 or more words is highlighted in amber. Long sentences are a leading cause of high readability scores because they raise the average words-per-sentence input used by the formulas.⁶ By surfacing each long sentence visually, the view lets you find the passages that drag your average down without re-reading the whole draft.

Turning highlights into revisions

To revise, click "Edit Text" to return to the textarea, shorten the flagged sentences, and watch the scores update automatically. A single long sentence in an otherwise short-sentence document can shift the Grade Level noticeably, so the threshold is intentionally conservative. Working from the highlighted list keeps your revisions focused and measurable.

After splitting or trimming each flagged sentence, re-check the scores to confirm the change moved the number in the right direction. Highlighting turns the abstract formula into a concrete set of edit decisions, so you can trust that each rewrite is working without reading the raw numbers every time. Iteration is the whole point of the feature.

Matching scores to your audience and content type

The right readability target depends on who will read your content and what they need from it. Marketing copy for a general consumer audience often benefits from a Reading Ease above 65 and a Grade Level below 9 because readers scan rather than study, and complex sentences make re-reading more likely. Specialist material can sit higher when precise terminology is part of the job.

SEO content, product documentation, and instructional guides each have different effective ranges. Product documentation for software developers often needs a higher grade level to describe APIs and configuration options accurately. Instructional guides for novices benefit from shorter sentences and familiar vocabulary because clarity matters more than precision. CapyToolkit calculates your score instantly as you type, so you can revise sentences, check the result, and converge on your target without switching between tools or submitting text to a remote API.