Readability Analyzer
Paste your content and get an instant readability analysis. Flesch-Kincaid scores, sentence structure, passive voice detection, and AI-specific readability checks — all in one place.
Why readability matters for AI
AI engines extract sentences, not pages
When ChatGPT, Perplexity, or Google AI Overview cites your content, it pulls individual sentences and short paragraphs — not entire pages. If your sentences are long and convoluted, AI engines struggle to find a clean excerpt. Short, clear sentences with one idea each are far more likely to be quoted in AI responses. Think of every sentence as a potential standalone answer.
Simpler words mean higher confidence
AI models process language probabilistically. Common, simple words have clearer meanings in context, which means AI can be more confident in its interpretation. Complex vocabulary, technical jargon, and multi-syllable words increase ambiguity. The Flesch-Kincaid Reading Ease score measures this directly: content scoring 60 or above (8th-9th grade level) hits the sweet spot where language is clear enough for AI to parse confidently, yet substantive enough to be worth citing.
Active voice is easier to attribute
Passive voice obscures who is doing what. “The study was conducted by researchers at MIT” is harder for AI to parse than “MIT researchers conducted the study.” Active voice gives AI engines a clear subject-verb-object structure they can confidently attribute and cite. Content with less than 10% passive voice is significantly easier for AI to extract clean, attributable statements from.
Sentence variety signals quality
A wall of uniformly long sentences signals dense, potentially academic content that is harder to parse. A mix of short and long sentences — short for key points, longer for elaboration — creates natural rhythm that is easier for both humans and AI to process. This variety also gives AI more options: it can pull a short sentence as a concise answer or a longer one for a more detailed response.
Structure is a readability multiplier
Even well-written prose becomes unreadable as a wall of text. Headings, lists, and short paragraphs create visual and semantic structure that AI engines use to navigate your content. Question-format headings (like “What is readability?”) directly match how users query AI engines, making your content discoverable. Lists are among the most commonly extracted content formats because they present information in a pre-structured way AI can immediately reuse.
Readability affects ranking, not just extraction
It is not just about whether AI can read your content — it is about whether AI chooses to. When multiple sources answer the same question, AI engines prefer the source that is clearest, most structured, and easiest to excerpt. A page with a grade 8 reading level and clear structure will be cited over a grade 14 page with the same information but denser prose. Readability is a competitive advantage.
Understanding the Flesch-Kincaid scores
Reading Ease Score (0-100)
Grade Level
The ideal range for AI-optimized content is grade 7-9: accessible to a broad audience while remaining substantive enough to cite.
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