LLM Visibility · Heavy
Will ChatGPT or Claude understand your content?
Chexter compares raw and rendered content, evaluates LLM content extraction quality, and checks trust signals: structure, authorship, and citability.
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Methodology
How LLM Visibility works
Is the key content in raw HTML — or hidden behind JS? LLMs typically cannot execute JavaScript.
Is the extracted text clean, coherent, and semantically meaningful? Or is it fragmented by nav/footer noise?
Clear H1–H3 hierarchy, logical sections, and short paragraphs help LLMs identify the main topic.
Author info, publication date, organization data, and About/Contact pages signal credibility to AI.
Presence of named entities (people, places, organizations, products) improves AI comprehension.
What LLM Visibility checks
Why use Chexter LLM Visibility
Frequently Asked Questions
What is LLM Visibility?
LLM Visibility measures how well language model–based AI systems (ChatGPT, Perplexity, Claude, Gemini) can extract and understand your page content — and whether they're likely to cite it.
Why can't AI read my JavaScript-rendered content?
Most AI crawlers fetch raw HTML without executing JavaScript. If your main content is injected by React, Vue, or similar frameworks, it's invisible to AI systems.
How does AI visibility differ from SEO?
SEO optimizes for keyword ranking in traditional search. AI visibility optimizes for content clarity, structure, and trust signals that make LLMs more likely to cite your content in answers.
What is a good LLM Visibility score?
Scores above 70 indicate strong AI readiness. Scores below 50 suggest structural or trust issues that prevent effective AI extraction.
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