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The highest-confidence tools. Both grounded in published studies with quantifiable output metrics.
Statistics, citations, quotations, and readability combined into a single 0–100 score. The highest-confidence tool — anchored in Aggarwal et al. 2024, peer-reviewed.
Open tool →Six structural absorption dimensions linked to AI answer absorption probability. Directional guidance — source is Zhang et al. 2026 preprint, clearly labelled.
Open tool →Heading structure and readability properties that published research links to AI citation frequency.
Flesch-Kincaid grade, passive voice rate, and sentence length distribution — with a bar chart showing where your content sits.
Open tool →Heading hierarchy charted as a tree. See structural richness and depth at a glance — mapped against structural absorption dimension patterns from published research.
Open tool →Entity coverage, platform-specific citation differences, and sentence-level extraction probability.
Named entity density and position mapped across your content — see what AI systems have to anchor their answers on.
Open tool →How ChatGPT, Perplexity, and Google AI Overviews differ in citation behaviour — so you know which platform to optimise for first.
Open tool →Sentence-level extraction probability, highlighted in place. See exactly which sentences AI systems are most likely to pull into answers.
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