Developer builds AI-readiness scanner that separates missing features from broken ones

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A developer has created an open scanner tool to honestly assess how well websites support emerging agentic web protocols, motivated by frustration with misleading 'AI readiness scores' that conflate absent features with genuinely broken implementations. The tool organises checks across six categories covering 30 technologies, deliberately scoring only 23 and leaving 7 unscored to avoid manufacturing false urgency. A core design rule ensures that if a protocol is not present on a page, no validation or scoring is performed at all, preventing absent-but-irrelevant features from dragging down results. Built on Lumar's custom metric infrastructure, it separates page-level signals checked per URL from site-wide signals fetched only once per host to avoid hammering servers during large crawls. The project also aims to bridge the gap between identifying what is broken and helping teams actually fix it, addressing a common bottleneck between SEO teams and engineering backlogs.

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