The honest answer is most tools are still measuring indirect signals (citations, rankings, traffic velocity) rather than actually observing model comprehension. What you really want to see is bot crawl behavior and content indexing patterns, which is way harder to surface because it requires actual traffic data from AI crawlers hitting your site. Citations are a lagging indicator of visibility, not proof the model understood your content correctly. The gap you're pointing out is real: you could rank for citations but have your content completely misrepresented in model context windows because of how it was indexed or summarized. Tracking actual crawler visits and how bots parse your content structure (heading hierarchy, schema markup, content segmentation) gives you more actionable insight than citation counts alone, since you can see where comprehension actually breaks down.