Works with articles, essays, emails, marketing copy, academic papers — any plain text.
Ready to analyze
Paste text and click Analyze to see complexity metrics// measure lexical density, sentence length & vocabulary richness
Measure lexical density, average sentence length, vocabulary richness, and overall complexity of any text. Free browser-based readability analyzer.
Ready to analyze
Paste text and click Analyze to see complexity metricsCopy any text — article, email, essay, or document — and paste it into the input area.
Hit the Analyze button. All processing happens in your browser instantly.
Explore the complexity score, lexical density, Flesch score, top content words, and all detailed metrics.
Text complexity measures how difficult a piece of writing is to read and understand. It combines factors like sentence length, word choice, vocabulary variety, and the proportion of content words to function words (lexical density).
Lexical density is the percentage of content words (nouns, verbs, adjectives, adverbs) relative to all words in a text. Higher lexical density (above 50%) indicates more information-dense writing, typical of academic or technical texts. Conversational text usually has lexical density of 40–55%.
TTR (also called Vocabulary Richness) measures how many unique words appear relative to total words. A higher TTR means greater vocabulary variety. A score of 70% means 70 out of every 100 words are distinct. Literary texts tend to have high TTR; repetitive writing scores lower.
The Flesch Reading Ease formula gives a score from 0 to 100. Higher scores mean easier reading: 90–100 is very easy (5th grade), 60–70 is standard (8th–9th grade), and below 30 is very difficult (college graduate). It's based on average sentence length and average number of syllables per word.
It depends on your audience. General blog posts and consumer content work best at 25–45 (Simple to Moderate). Professional reports and news articles typically score 45–65. Academic papers and legal documents often range 65–85. Match complexity to what your readers expect and can process comfortably.
No. All analysis is performed entirely in your browser. Your text never leaves your device and is not stored, logged, or transmitted to any external server. This makes it safe for analyzing confidential or sensitive documents.
For meaningful metrics, we recommend at least 100 words. Shorter texts can produce misleading TTR and lexical density scores because statistical measures work more reliably on larger samples. For best results, paste at least 200–300 words.
A text complexity scorer is an analytical tool that evaluates how difficult a piece of writing is to read and understand. Unlike simple word counters, a complexity scorer examines multiple linguistic dimensions simultaneously — including sentence length, vocabulary richness, syllable density, and the proportion of content-bearing words in the text. The result is a comprehensive profile of your writing that helps you calibrate it for a specific audience.
Whether you're a content writer trying to make your articles more accessible, an academic fine-tuning a research paper, or a marketer crafting email copy for a broad audience, understanding your text's complexity lets you make smarter editorial decisions.
💡 Looking for premium web development assets? MonsterONE offers unlimited downloads of templates, UI kits, and writing-focused themes — worth checking out.
Lexical density is one of the most telling measures of text complexity. It's defined as the ratio of content words — nouns, main verbs, adjectives, and adverbs — to all words in a text, expressed as a percentage.
Academic and technical writing typically achieves lexical density of 55–65%, packing a high proportion of meaning-carrying words into each sentence. Casual conversation and simple instructional text usually falls between 35–50%. When a text's lexical density is very high, readers must process more information per sentence, which increases cognitive load and perceived difficulty.
For most web content targeting a general audience, aiming for lexical density in the 45–55% range strikes a good balance between informativeness and readability.
The Type-Token Ratio (TTR) measures vocabulary richness — the proportion of unique word forms (types) relative to total word occurrences (tokens). A TTR of 80% means 80 out of every 100 words are distinct; a TTR of 40% indicates significant word repetition.
High TTR signals sophisticated, varied writing that demonstrates command of language. However, very high TTR isn't always better — some repetition serves clarity and helps readers follow key concepts. Technical documentation often intentionally repeats terminology for precision. Literary writing, by contrast, achieves high TTR through deliberate vocabulary variation.
Note that TTR is sensitive to text length: shorter texts naturally score higher because they have fewer opportunities to repeat words. For fair comparisons, always compare texts of similar length.
Sentence length is one of the oldest and most reliable predictors of reading difficulty. Long sentences require readers to hold more information in working memory before they can process the complete thought. Short sentences are processed faster and feel more punchy and direct.
Most readability researchers suggest an average sentence length of 15–20 words for general audiences. Academic prose routinely averages 25–35 words per sentence. Journalistic writing, especially news leads, targets 12–15 words. For the web, shorter tends to be better — screen reading is cognitively more demanding than reading print.
Developed by Rudolf Flesch in 1948, the Flesch Reading Ease formula remains the most widely used automated readability measure. It calculates a score from 0 to 100 using two variables: average sentence length (in words) and average number of syllables per word.
While the Flesch formula is a useful benchmark, it doesn't capture every dimension of readability. Familiarity with the subject matter, background knowledge, and formatting all affect comprehension in ways the formula can't measure. Use it as one signal among many.
Our overall complexity score synthesizes multiple metrics into a single 0–100 index. The algorithm weighs Flesch Reading Ease (inverse), average sentence length, lexical density, vocabulary richness (inverse TTR), and the proportion of long words. The result gives you a quick, at-a-glance measure of how demanding your text will be for a typical reader.
Scores are categorized as: Very Simple (0–14), Simple (15–34), Moderate (35–54), Complex (55–74), and Very Complex (75–100). These labels aren't judgments — they're descriptors. A research paper should score in the Complex range; a product FAQ should aim for Simple to Moderate.
Content marketers can use complexity scoring to ensure blog posts and landing pages match their audience's reading level, reducing bounce rates and improving time on page.
Academics and students can verify that a paper meets the expected complexity level for its genre and publication venue, and spot overly complex or surprisingly simple passages.
UX writers can audit microcopy, onboarding flows, and help documentation to ensure clarity for all users, including those with lower literacy or non-native language skills.
SEO professionals can align content complexity with the search intent signals that Google uses when evaluating topical authority and content quality.