The agent successfully assembled a comprehensive explanation of omiid.me by combining a markdown-rendered homepage (step 14) with discovery metadata from a well-known agent endpoint (step 11). However, the site's client-side rendering made most HTML pages opaque—the agent could not fully explore the notebook or tool pages, forcing reliance on the homepage markdown and prior knowledge to fill gaps about specific projects and features.

• ›Step 14 (markdown homepage) was the primary content source: it clearly stated Omid's role ('Senior software engineer in Amsterdam'), his focus areas ('how AI changes engineering work'), and listed specific article titles. This single fetch answered ~70% of the task.
• ›Step 11 (.well-known/agent discovery endpoint) provided structural metadata and confirmed the site's agent-friendly capabilities (markdown representation, collections, skills index), but did not contain the substance about what omiid.me *does*—it was a routing/capability signal, not content.
• ›The site published rich markdown representations (step 14 was fetched as text/markdown), making it agent-accessible for the homepage, but most other pages (notebook index, tools, AI usage dashboard) returned only HTML bundles with no fallback, forcing the agent to infer content from URLs, web search results, and prior knowledge about the creator.
• ›The agent discovered the markdown homepage serendipitously: it fetched the HTML version twice (steps 1, 8) unsuccessfully, then on step 14 received markdown without explicitly requesting a content-type override—suggesting the site may negotiate format via Accept headers or the agent used prior knowledge to guess the markdown representation.
• ›Gaps in coverage: the notebook index, Smoketest project details, pgvector course, cron tool, and AI usage metrics remained invisible because their pages were HTML-only. The agent filled these from web search snippets (step 6) and prior knowledge, not from direct navigation.