AI Text Analyzer — Pattern & Style Metrics
Analyze text patterns: sentence variation, vocabulary diversity, repetition, and burstiness scores. Free writing analysis tool.
About AI Text Analyzer
This tool analyzes text using statistical metrics that reveal writing patterns. Burstiness measures sentence length variation — human writing tends to have more varied sentence lengths, while AI-generated text often has more uniform patterns.
The analyzer calculates vocabulary diversity, repetition rates, average sentence length, and other metrics. It does not use AI to classify text — it provides objective statistics that you can interpret yourself.
Text analysis metrics like burstiness and vocabulary diversity originated in computational linguistics research. Burstiness quantifies how much sentence lengths vary throughout a document — a score near 1.0 indicates highly varied sentence lengths typical of natural human writing, while scores near 0 suggest uniform, predictable patterns. Vocabulary diversity is calculated as the ratio of unique words to total words (type-token ratio).
Content editors use text analysis to evaluate draft quality before publication. By reviewing average sentence length (target: 15-20 words for web content) and repetition scores, writers can identify passages that feel monotonous or overly complex. Pair this analyzer with the Readability Checker for a complete picture of your text's accessibility.
All analysis runs client-side using JavaScript string processing. No text is sent to any server, making this tool suitable for analyzing confidential documents, legal drafts, or proprietary content. The results update in real time as you type or edit.
How the AI Text Analyzer Works
- Paste your text into the analysis area
- The tool evaluates vocabulary complexity, sentence structure, and readability
- View metrics like word count, average sentence length, and unique word ratio
- Get a summary of the text's overall complexity level
Text Complexity and Audience Matching
Matching your writing complexity to your audience is critical for engagement. Academic papers typically score at grade 12+ readability, while popular web content targets grade 6-8. High vocabulary diversity (many unique words) suggests sophisticated writing but can reduce accessibility. Average sentence length above 25 words usually signals text that's hard to follow — aim for 15-20 words per sentence for general audiences.
When to Use the AI Text Analyzer
Use this tool when you need objective measurements of writing complexity and style. It is particularly useful for evaluating draft content before publication, comparing the writing style of different authors, or analyzing text for consistency across a large document. Content teams use it to ensure articles match a target complexity level for their audience.
Common Use Cases
- •Evaluating content readability before publishing blog posts or documentation Readability Checker — Flesch Score & More
- •Comparing writing styles between multiple authors or content sources
- •Checking AI-generated drafts for naturalness and variety AI Content Detector — Free Text Analysis
- •Analyzing academic papers for vocabulary complexity and sentence structure
Expert Tips
- ✱Aim for an average sentence length of 15-20 words for web content and 20-25 words for academic writing.
- ✱A burstiness score above 0.5 generally indicates engaging, varied writing that holds reader attention.
- ✱Check repetition scores after editing to ensure you haven't introduced redundant phrasing during revisions.
Frequently Asked Questions
- Burstiness measures the variation in sentence lengths throughout your text. A high burstiness score means sentence lengths vary significantly — some short, some long — which is typical of natural human writing. A low score indicates uniform sentence lengths, which can make text feel monotonous. The score is calculated as the standard deviation of sentence lengths divided by the mean.
- Vocabulary diversity (type-token ratio) ranges from 0 to 1. General web content typically scores 0.4-0.6. Academic writing scores 0.6-0.8 due to specialized terminology. Fiction often scores lower (0.3-0.5) because narrative uses common words repeatedly. A score above 0.7 suggests sophisticated vocabulary but may reduce accessibility for general audiences.
- This tool measures statistical text properties — it does not classify text as human or AI-written. However, the metrics it provides (burstiness, vocabulary diversity, repetition) are the same metrics used by AI detection tools. Low burstiness combined with moderate vocabulary diversity can indicate AI-generated text, but these patterns alone are not definitive proof.
- No. All analysis runs entirely in your browser using JavaScript. Your text never leaves your device, making this tool safe for confidential, legal, or proprietary content.
What does the burstiness score measure?▾
What is a good vocabulary diversity score?▾
Can this tool detect AI-generated text?▾
Is my text stored or sent to a server?▾
Related Tools
AI Token Counter — GPT, Claude & Gemini
Count tokens for GPT, Claude, Gemini, and other AI models. Estimate costs per API call with built-in pricing. Free online tool.
AI Model Comparison — 50+ Models Side by Side
Compare 50+ AI models: pricing, context windows, capabilities, and benchmarks. Filter by provider, open source, and features.
AI Content Detector — Free Text Analysis
Analyze text for AI-generated patterns using perplexity, burstiness, and vocabulary diversity. Free, private — runs entirely in your browser.
AI Prompt Generator — Structured Builder
Build structured prompts for ChatGPT, Claude, and other AI models. Select role, task, context, and format. Free prompt engineering tool.
AI Image Prompt Builder — Midjourney & More
Build prompts for Midjourney, DALL-E, Stable Diffusion, and Flux. Style, lighting, and composition controls. Free prompt tool.
System Prompt Builder — AI Instructions
Build structured system prompts for ChatGPT, Claude, and other AI models. Model-specific export formats. Free prompt builder.
Learn More
AI Tools Every Developer Should Know in 2026: Tokens, Prompts, and Model Selection
A practical guide to AI development tools: understanding tokens, writing effective prompts, comparing models, and optimizing costs for LLM-powered applications.
AI Content Detection & Analysis: How to Verify, Analyze, and Improve AI-Generated Text
Learn how to detect AI-generated content, analyze text quality, and use AI writing tools responsibly. Covers content detection, text analysis, readability checking, and prompt engineering.