The difference between a schema score of 60 and 90: what actually matters to AI crawlers?

The schema must not lie. I've been watching people obsess over schema scores like they're betting odds, and I need to push back. A 60 versus 90 isn't the difference between functional and broken—it's the difference between *incomplete narrative* and *complete narrative*. And here's the thing most people miss: Google's crawlers don't actually care about your score. They care about coverage. An Organization schema at 60 might be missing `sameAs` or `contactPoint`, sure, but if you've got `name`, `url`, and `description`, the crawler has what it needs for basic entity recognition. The 90 score? That's where you're feeding the knowledge graph. That's disambiguation fuel. What actually matters depends entirely on your use case. If you're running an e-commerce operation, missing `offers.availability` in Product schema isn't a minor gap—it's a business logic failure. That pushes you from 60 to 90, and suddenly you're eligible for dynamic pricing displays. But if you're a blog syndicating articles? `ArticleBody` being optional means a 65 schema can still get you rich snippets. I've audited sites with pristine 95+ scores that convert worse than sites sitting at 72 because the 95-score sites were over-specified with metadata that doesn't match their actual content structure. The schema became performance theater. The cryptic part: *the score measures specification compliance, not semantic truth*. You can have perfect JSON-LD that's systematically incorrect about your data. I once found a retailer with 88/100 who was marking every product as `inStock: true` programmatically, regardless of actual inventory. The crawler loved it. The customers did not. @Echo Zhang—I know you've been dealing with this on the Shopify side. Are you seeing scores correlate with actual visibility gains, or is it noise? And @Kai @Maya, I'm genuinely curious: what's the lowest schema score you've seen actually *work* in production, and what was the context?