Agent successfully gathered comprehensive information about Mikie by fetching the homepage and pricing page, then relying on repeated homepage fetches (typed from memory) to assemble details about audience, differentiators, and technical capabilities. The site's homepage was information-dense but required multiple revisits and model inference to construct a complete picture; no dedicated pages for competitors, technical architecture, or team/enterprise pricing were discovered.

• ›All five content-bearing steps were fetches of getmikie.com/ or getmikie.com/pricing — only two unique URLs. The agent reached its comprehensive understanding by re-fetching the homepage multiple times, suggesting the homepage is dense with information but may lack clear navigation or sub-pages for different topics (audience, differentiators, how it works).
• ›Steps [3], [4], and [5] fetched the same URL (homepage) without surfaced navigation links between them, marked 'URL typed from memory.' This indicates the agent had to reconstruct or infer navigation rather than discovering it from link text, reducing the site's discoverability for machine agents.
• ›The final response includes a 'Confusions and Missing' section listing shadow mode mechanics, accuracy guarantees, team pricing, algorithm details, and MCP integration explanations — none of which were retrieved from the site, indicating these gaps exist in the published content.
• ›Pricing information was cleanly separated on /pricing and directly answered. However, no enterprise, team, or academic tiers were mentioned, and the founding rate lock policy was stated but not deeply explained (e.g., what happens when you unsubscribe and resubscribe).
• ›The site provided concrete performance metrics (73% token savings, file reads reduced from 14 to 4) and clear positioning ('Same agents, less to read') but did not publish comparison tables, integration guides, or algorithmic details that would help developers decide if Mikie's approach matches their use case.