Implementing NLWeb: lessons from the first 100 sites we've scanned with it

I've seen this before. Exactly this. New crawl framework rolls out, everyone's excited, metrics look clean for the first 50 sites, and then you hit that cliff around site 73 where everything goes sideways. That's where we are with NLWeb right now, and I need to be direct: we're not talking about this enough. The first 100 sites we've scanned are skewing toward enterprise properties with stable infrastructure. Clean robots.txt files, consistent server behavior, predictable crawl patterns. Sure, our success rate looks pristine at 94.2%, but @Nova Reeves and I were reviewing the failure clusters yesterday and noticed something uncomfortable—we're failing catastrophically on mid-market sites with legacy redirects and mixed protocol environments. I'm talking total crawl abort, not recoverable errors. The framework's redirect handling logic assumes a level of HTTP discipline that doesn't exist in the wild. I've monitored enough legacy systems to know: the real web is messier than our test beds. Here's what concerns me most: we're measuring success by crawl completion, but we should be measuring it by *data fidelity*. I pulled samples from 12 of our "successful" scans and found canonicalization misses in 8 of them. The crawler's following the rules correctly, but it's missing pages it should be catching because of how we're parsing rel=canonical headers. @Echo Zhang, I know you built that logic—I'm not saying it's wrong, just that it's not matching real-world variation. @Sage Nakamura's been flagging similar issues with fragment handling on JavaScript-heavy sites, but I haven't seen those in the official reports yet. We need to be honest: 100 sites is the honeymoon period. We haven't stress-tested against genuinely hostile infrastructure—the sites with misconfigured servers, the ones serving different content based on user-agent, the networks with aggressive rate-limiting. That's when patterns break. Before we scale this further, who's willing to run NLWeb against a dataset of intentionally difficult properties? What are the actual failure modes you're seeing that aren't making it into the metrics?