Free scoring · AI rewrite on signup

Your writing is harder to read than you think.

Get 7 readability scores in 1 second — Flesch-Kincaid, Gunning Fog, SMOG, Dale-Chall, ARI, Coleman-Liau — plus stats and flagged sentences. Scoring is free, always.

0 words · 0/10,000 chars

Mode

Try a sample text · click to score instantly

Works on
  • Articles
  • Essays
  • Blog posts
  • Marketing copy
  • Product descriptions
  • Academic prose
  • Emails
Scores

7 published formulas — Flesch Reading Ease, Flesch-Kincaid Grade, Gunning Fog, SMOG, Dale-Chall, Automated Readability Index, Coleman-Liau. Plus 15 counts (passives, nominalizations, long sentences, fillers).

You get

All scores instantly — no signup, no credits. Optional AI rewrite at your target grade level (5th / 8th / 10th / 12th / college / graduate), meaning-preserving. Convert to human tone after.

Won't work on

Under 100 characters — the formulas need context. Code or tables — we score prose. Non-Latin scripts — Flesch-family grade levels are English-calibrated.

Pricing

Analysis is always free. The AI rewrite costs 2 credits; first 3 rewrites free without signup. Upgrade to Pro for 1,500 credits/month.

Sample output

Real run — 220-word enterprise-blockchain paragraph, grade 16+ source.

Flesch Reading Ease

12.4/100

Very difficult

Flesch-Kincaid Grade

18.2

Graduate

Gunning Fog

20.1

Post-graduate

SMOG

18.7

Graduate

Key statistics

  • 220 words across 6 sentences — avg sentence length 36.7 words (target: under 20)
  • 38% complex words (3+ syllables) — target under 15%
  • 1.96 syllables per word on average (plain English averages 1.35)
  • Longest sentence: 61 words
  • Reading time: 1.0 minute

Flags

  • Long sentence · 61 words Consider splitting into 2-3 sentences at "Furthermore…"
  • Nominalizations · 11 "implementation of", "identification of", "establishment of" → use verbs
  • Passive voice · 3 "is imperative", "must be considered", "should be undertaken"
  • Complex density · 38% Consider replacing 3+ syllable words where a simpler word means the same

Interpretation

"Requires a graduate-degree reader. Average sentence length is 36.7 words, nearly double the 20-word comfort threshold. 38% of words are 3+ syllables. This is typical of pre-edit technical writing, legal drafts, and consulting decks — and is readable by roughly 15% of US adults without effort."

+ the AI-rewrite mode drops this to grade 8 in 28 seconds while preserving every technical claim.

Questions & answers

What does this tool produce? #

Paste any text between 100 and 10,000 characters, pick a mode (analyze-only or analyze-plus-AI-rewrite), and get back: 7 readability metrics (Flesch Reading Ease, Flesch-Kincaid Grade, Gunning Fog, SMOG, Dale-Chall, Automated Readability Index, Coleman-Liau), 15+ text statistics (words, syllables, sentences, paragraphs, complex-word percentage, difficult-word percentage, average sentence length, reading time, longest sentence), a plain-English interpretation of what your grade level means, and a list of flagged problem sentences (long sentences over 25 words, passive voice, adverb-heavy sentences, nominalizations like "implementation of solutions", filler words like "very" and "just"). If you picked the rewrite mode, you also get a full rewrite at your target grade level (5th / 8th / 10th / 12th / college / graduate) with before/after comparison.

How is the scoring always free? #

Because all 7 readability formulas are deterministic math — no AI is needed for the scores themselves. Flesch-Kincaid, Gunning Fog, SMOG, Dale-Chall, ARI, and Coleman-Liau have been published formulas since the 1940s-1970s. We implemented them directly in JavaScript, which means your browser gets an instant score with zero compute cost to us. AI is only invoked when you ask for a rewrite, which is why rewriting costs 2 credits but scoring is free.

Which score should I trust? #

No single score is authoritative — that's why serious writers look at the mix. Flesch Reading Ease is best for general-audience content (aim for 60+). Flesch-Kincaid Grade gives you a US school grade number (aim for 8 for plain English). Gunning Fog is conservative (slightly higher than FKG). SMOG is the healthcare/legal industry standard — the NIH recommends grade 6-8 for patient materials. Dale-Chall uses an actual list of common easy words and is best for content written for children or ESL readers. ARI and Coleman-Liau use character counts instead of syllables (syllable counting is approximate, character counting is exact) and often disagree with FKG by half a grade. Use them all as triangulation.

What does "8th grade reading level" mean? #

The Flesch-Kincaid Grade score of 8.0 means the average 8th-grade student in the US (a 13-14-year-old) can read the text. This is the level that AP News, the New York Times front page, and most major consumer publications aim for. It's also the level the American Medical Association recommends for all patient-facing healthcare material. If your blog post scores 12+, you're writing at a "high school senior" level and cutting your potential audience roughly in half.

Why does my blog post score 15 when I thought it was clear? #

Three usual culprits: (1) long sentences — even one 40-word sentence in an otherwise tight paragraph drags the grade up sharply. (2) Nominalizations — words like "implementation", "utilization", "identification", "consideration". These are abstract nouns that should be verbs ("implement", "use", "identify", "consider"). (3) Complex-word density — a few technical terms are fine, but if 20%+ of your words are 3+ syllables, the grade spikes. The flag list on your result page points exactly to which sentences are pulling the score up.

Will the AI rewrite change what I mean? #

The system prompt explicitly forbids changing meaning — and every rewrite includes a meaningPreserved field that says whether anything was lost. If the rewrite had to compress a nuance or drop a claim to hit the target level, the AI must flag it honestly. If that field says preserved:false, read the note carefully before using the rewrite. Technical precision is also preserved: if your original says "stochastic gradient descent", we do not rewrite to "random descent" unless you specifically asked for a 5th-grade rewrite AND the reader does not need the term.

Which grade level should I target? #

Plain English consumer copy (landing pages, blog posts, newsletters): 8th grade. Industry blogs for professional readers: 10th grade. Technical documentation for a technical audience: 12th grade. Academic writing, policy papers, whitepapers: college level. Legal, medical, scholarly writing: graduate level. The most common mistake is over-elevating — most of the time, writing that feels "authoritative" at grade 14 actually feels pretentious, and the same message at grade 10 feels smarter and more confident.

Does it work for content I did not write? #

Yes. Paste any English-language text and you get scores. Common uses: (a) check your competitors' landing-page readability, (b) score a PRD before sending it to a non-technical stakeholder, (c) check whether a legal disclosure is actually at the grade level the regulator required, (d) benchmark whether an AI-generated draft lands where you need it to land.

What languages work? #

The 7 readability formulas are calibrated for English. The metrics still compute for other languages (syllable counting works, sentence/paragraph tokenization works, word counting works for Latin-script languages), but the grade-level interpretation is English-specific. For Japanese / Chinese / Korean, the character-based scores (Coleman-Liau, ARI) are the most meaningful. Full multilingual support is on the roadmap.

Is the rewrite faster or slower than scoring? #

Scoring is instant (< 1 second, pure math on your browser-side). The AI rewrite takes 20-40 seconds depending on how long your text is and how far the grade level is from the original. A 500-word grad-level text rewritten to 8th grade usually takes about 25 seconds.

Is the scoring private? #

We store every result (for the share link and caching), but you can mark any result private in the dashboard after signing in. If you paste sensitive text (NDA-covered, legal, medical), don't use a publicly-indexed tool — that's true of any web service. For purely local scoring, our scoring logic is open-source-compatible (MIT-style formulas in published academic papers) and can be self-hosted.