AINew

AI Readability Score

Calculate rule-based readability scores for your content

100% client-side — your data never leaves your browserNo data stored or uploadedFree for lifetime · No signup

What this tool calculates

This tool runs five classic, rule-based readability formulas on your text: Flesch Reading Ease (0-100, higher is easier), Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, and the Automated Readability Index. Each formula combines sentence length, word length, and syllable counts (estimated with a vowel-cluster heuristic, not a dictionary) into a single number that approximates the US school grade level needed to comprehend the text.

Despite the name, none of these formulas involve a language model — they're the same deterministic equations that have been used in publishing and education since the 1970s. "AI" readability here refers to a common use case: checking whether content written by or for an AI system (chatbot responses, generated articles) reads at an appropriate level, not that the scoring itself uses AI.

When to use it

Use it to check whether marketing copy, documentation, or support articles match your target audience's reading level — general consumer content usually aims for 60-70 Flesch Ease (8th-9th grade), while technical documentation can reasonably sit lower. It's also useful for auditing AI-generated content before publishing: LLM output often defaults to longer, more complex sentences than house style calls for, and a quick score flags pages that need simplifying.

Because five formulas run at once, look for agreement rather than trusting a single number — if Flesch-Kincaid says 8th grade but Gunning Fog says college level, the discrepancy usually means the text has a mix of short simple sentences and a few very long, jargon-heavy ones dragging the average.

Example

Paste "The rate limiter uses a token bucket algorithm to smooth bursty traffic while enforcing an average request rate." and expect a Flesch Ease in the 30s-40s (Difficult/College level) — driven by long words like "algorithm" and "enforcing" and a single dense sentence. Splitting it into two shorter sentences and swapping "utilizes" for "uses" (already done here) typically raises the score by 10-20 points.

How to use the AI Readability Score tool

  1. 1

    Paste your content

    Full paragraphs work better than single sentences — the formulas need enough words and sentences to average over.

  2. 2

    Click Analyze

    All five scores compute at once, plus an overall grade-level label based on Flesch Ease.

  3. 3

    Compare the scores

    If the five formulas disagree significantly, look for a mix of very long and very short sentences.

  4. 4

    Share the result

    Copy a permalink so a teammate or editor sees the same scores for the same draft.

Frequently asked questions

Why do the different scores disagree?

Each formula weights sentence length, word length, and syllables differently, and syllables are estimated with a heuristic rather than a dictionary lookup, so irregular words can skew any single score. Treat the scores as a directional signal, not an exact grade-level guarantee.

Does this analyze AI-generated text differently than human-written text?

No — the formulas are text-agnostic and don't detect or care whether content was AI-generated. The name reflects a common use case (grading AI output before publishing), not a different scoring method.

What's a good target score for web content?

Most consumer-facing web copy targets Flesch Reading Ease 60-70 (roughly 8th-9th grade). Technical audiences (developer docs, legal, academic) commonly score lower and that's expected — match the level to your actual readers, not a universal target.

Is my content sent anywhere?

No. All scoring runs client-side in your browser with plain JavaScript — nothing is uploaded or logged.

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