Readability Checker: Analyze Text Score

What Is Readability Checker?

The Readability Checker analyzes text using eight industry-standard readability formulas and returns an overall reading level alongside individual scores. It surfaces metrics used by publishers, educators, content strategists, and UX writers to match writing complexity to a target audience. All calculations run locally in your browser via a web worker — no text is uploaded, no account is required. Use it to audit blog posts, legal disclaimers, product descriptions, academic abstracts, or any text where the complexity level affects how well readers engage and comprehend.

Key Features

• Flesch Reading Ease score — A 0–100 scale where higher means easier. Scores ≥ 90 indicate very easy text (5th grade), scores < 30 indicate very difficult (professional/academic).
• Flesch-Kincaid Grade Level — Maps text complexity to a US school grade; grade ≤ 6 is easy, grade > 12 targets college-level readers and above.
• Gunning Fog Index — Estimates the years of formal education needed to understand the text on first reading; scores above 12 are considered difficult.
• Coleman-Liau Index — Uses character counts per word and sentence rather than syllables, making it suitable for programmatic analysis.
• SMOG Index — Counts polysyllabic words (3+ syllables) and is particularly reliable for health literacy assessments.
• Automated Readability Index (ARI) — Based on characters per word and words per sentence; the copy output includes ARI alongside the other scores.
• Linsear Write Formula — Designed for technical writing; weights easy words (≤2 syllables) and hard words (3+ syllables) separately.
• Dale-Chall Readability Score — Uses a list of familiar words; scores below 5.0 are very easy, scores 9.0–9.9 are difficult, and scores 10.0 or above are very difficult. Uses its own rating scale distinct from grade levels.
• Overall reading level recommendation — Derived from the Flesch Reading Ease score; displayed prominently at the top with a color-coded label.
• Hemingway Mode — Highlights sentences by issue type: very long sentences (>40 words, red), long sentences (>25 words, yellow), passive voice constructions (blue), and adverb usage (green).
• Real-time analysis — Calculations run in a web worker with debouncing; a spinner indicates when processing is active.
• Non-Latin text warning — A yellow warning card appears when the input contains characters outside the Latin Extended Unicode range (U+0000–U+024F, U+1E00–U+1EFF), since the formulas are designed for English text.

How to Use Readability Checker

Step 1: Paste or type your text

Scroll to the input card labeled "Enter Text" and paste your content into the textarea. The field accepts any length of text. A word count is shown beside the label and updates as you type. The tool requires a minimum number of words before displaying scores; if the input is too short, the reading level card shows a message indicating this.

Step 2: Review the overall reading level

The first card shows the overall reading level derived from the Flesch Reading Ease score. The level uses color-coded labels:

Below the level label, the tool shows the textStandard value — a consensus grade-level estimate derived from all eight scores combined.

Step 3: Examine the detailed scores grid

The Detailed Scores card displays all eight metrics in a 4-column grid. Each ScoreCard shows the numeric value rounded to one decimal place, the formula name, a difficulty label with color coding, and an info tooltip with a plain-English description of what the formula measures. Use this grid to compare how different formulas rate the same text — divergence between formulas can indicate stylistic features worth investigating.

Step 4: Enable Hemingway Mode

Click the "Hemingway Mode" toggle button above the textarea. The input text remains editable, but a highlighted overlay appears beneath it showing sentences color-coded by issue:

• Red highlight — Very long sentences (more than 40 words)
• Yellow highlight — Long sentences (more than 25 words)
• Blue highlight — Passive voice constructions (detected by the pattern is/are/was/were/be/been/being + past participle)
• Green highlight — Sentences containing adverbs (words ending in -ly)

A legend below the overlay identifies each color. This mode helps you identify specific sentences to revise rather than just seeing aggregate scores.

Step 5: Copy the scores or clear the input

Click "Copy Scores" to copy all eight formula values and the overall reading level in a formatted text block. Click "Clear" to reset the input. The Clear button is disabled when the textarea is empty to prevent redundant actions.

Practical Examples

Auditing a user-facing error message

A UX writer reviews the text: "The operation could not be completed successfully due to an unrecoverable internal server error." Pasting this single sentence produces a high grade-level score because of "unrecoverable" and "successfully" — long polysyllabic words the SMOG and Gunning Fog formulas penalize. The writer revises to "Something went wrong. Please try again." and confirms the new score drops to a Very Easy / 5th grade level.

Checking a health information brochure

A public health organization requires all patient materials to score at or below a 6th-grade Flesch-Kincaid level. The writer pastes a paragraph from a pamphlet about medication instructions and checks the Flesch-Kincaid Grade Level card. If it reads 8.2, the writer uses Hemingway Mode to identify which long sentences are driving the score up and rewrites them.

Reviewing an academic abstract

A researcher wants to confirm an abstract written for a general science audience is not too dense. Pasting 250 words of abstract text shows a Gunning Fog Index of 16.4 — equivalent to college-senior level. The Hemingway Mode highlights several very-long sentences (red) and four passive-voice constructions (blue), giving specific targets for revision.

Tips and Best Practices

Aim for consistency across formulas. When the Flesch Reading Ease and Gunning Fog disagree significantly, the text may have an unusual structure — many short words in very long sentences, or many polysyllabic words in short sentences. Look at the Hemingway Mode highlights to diagnose which pattern is responsible.

The non-Latin warning is important. All eight formulas rely on syllable counts and word complexity heuristics calibrated for English. If you paste text containing Chinese, Arabic, Greek, or Cyrillic characters, the tool displays a yellow warning card. Results for non-Latin text are not meaningful and should be disregarded.

Very short texts produce unreliable scores. Readability formulas require enough sentences and words to produce statistically stable averages. Single sentences or very short paragraphs will generate extreme scores. Use texts of at least 100 words for reliable results.

Hemingway Mode detects -ly adverbs broadly. The adverb detection regex matches any word ending in -ly, which includes non-adverb words such as "family," "only," and "early." Treat green highlights as candidates for review rather than definitive identifications of problematic adverbs.

Copy Scores for documentation. Use the Copy Scores button to capture a snapshot of all eight scores at once. This is useful for content audits, before/after comparisons, or embedding scores in editorial guidelines.

Common Issues and Troubleshooting

Scores do not appear after pasting text. The tool requires a minimum word count before displaying scores. If the input is below the threshold, the reading level card shows "Enter more text to analyze" (or equivalent). Add more content until at least a few sentences are present.

The spinner stays visible for a long time. The tool uses a web worker with debouncing to handle large texts without blocking the UI. For very large inputs, the isLargeText flag triggers a blue informational card showing the word count and indicating that analysis may take a moment. If the spinner persists indefinitely, try refreshing the page.

Hemingway Mode passive voice detection misses some constructions. The pattern /\b(is|are|was|were|be|been|being)\s+\w+ed\b/i catches common regular-verb passive constructions but will miss irregular past participles such as "written," "broken," or "spoken." A sentence like "The report was written by the committee" will not be highlighted in blue.

Non-English text shows a disclaimer. When the UI language is set to a non-English locale, an amber warning card appears at the top reminding you that the formulas are designed for English. Results for other languages are unreliable and provided only as a rough reference.

Privacy and Security

The Readability Checker processes all text locally using a browser web worker — no content leaves your device. The tool performs no network requests during analysis. This makes it safe to analyze confidential content such as internal memos, legal drafts, medical documentation, or proprietary product descriptions. The tool works offline once the page has loaded and cached in your browser.

Frequently Asked Questions

Is Readability Checker free to use?

Yes. The Readability Checker is completely free. All eight scoring formulas, Hemingway Mode, and copy functionality are available without an account or payment.

Does Readability Checker work offline?

Yes. All calculations run in a browser web worker with no external API calls. Once the page is loaded and cached, you can use the tool without an internet connection.

Is my data safe with Readability Checker?

Your text is never sent to any server. All analysis happens locally via a JavaScript web worker embedded in the page. It is safe to analyze sensitive, proprietary, or personally identifiable text.

What is the Flesch Reading Ease score?

Flesch Reading Ease is a 0–100 numeric score developed by Rudolf Flesch in 1948. Higher scores mean easier text. Scores of 60–70 are suitable for general adult audiences. Scores above 80 target 6th-grade reading level or lower, which is recommended for consumer-facing content. Scores below 30 are typically found in academic journals and legal documents.

What is the Gunning Fog Index?

The Gunning Fog Index, developed by Robert Gunning in 1952, estimates the years of formal education required to understand a piece of text on first reading. A score of 12 corresponds to a high school senior level. Scores above 17 are considered beyond college level. The formula counts the percentage of "complex words" (three or more syllables) in each sentence.

How is the overall reading level determined?

The overall reading level label is derived from the Flesch Reading Ease score, which is displayed with a color-coded difficulty label. The textStandard value shown below it is a consensus estimate that combines all eight formulas into a single grade-level range, giving a more robust picture than any single metric.

What does Hemingway Mode do?

Hemingway Mode highlights sentences in the text with color-coded overlays based on potential readability issues: red for very long sentences (>40 words), yellow for long sentences (>25 words), blue for passive voice constructions, and green for sentences containing adverbs (words ending in -ly). It provides sentence-level diagnostic feedback rather than aggregate scores.

Which formula is best for my use case?

For general consumer content, use Flesch Reading Ease as the primary metric. For educational materials aligned to US school grades, use Flesch-Kincaid Grade Level. For health literacy assessments, SMOG Index is considered the most reliable. For technical documentation, Linsear Write Formula weights technical vocabulary (polysyllabic words) appropriately.

Does the tool support languages other than English?

The formulas are designed for English and produce unreliable results for other languages. The tool displays a yellow warning card when non-Latin characters are detected in the input. For non-English locales, an amber disclaimer card appears at the top of the page reminding users of this limitation.

How many scoring formulas does the tool use?

The tool runs eight formulas simultaneously: Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, SMOG Index, Automated Readability Index (ARI), Linsear Write Formula, and Dale-Chall Readability Score. Each uses a different mathematical approach and emphasizes different text characteristics.

Related Tools

• Syllable Counter — Counts syllables per word in a block of text; useful for understanding why formulas like SMOG and Gunning Fog rate your text as complex when many polysyllabic words are present.
• Word Counter — Counts words, characters, sentences, and paragraphs; provides the raw text statistics that readability formulas use as inputs.
• Character Counter — Measures character count and byte length; the Coleman-Liau Index is based on characters per word rather than syllables, making this tool a useful companion for understanding that score.

Try Readability Checker now: Glyph Widgets Readability Checker