The agent successfully assembled a comprehensive overview of Milbby by discovering and fetching four key pages—the homepage, About page, FAQs, and loyalty program page—though it had to rely on web search to locate pages beyond the homepage. The site was partially navigable: standard information architecture paths (e.g., /pages/about, /pages/pricing) returned 404s, forcing the agent to use search to find the correct URL structure (/pages/asi-somos instead of /pages/about). Once the correct URLs were located, the content-bearing pages delivered enough information to explain what Milbby does, who it's for, and how it differs from alternatives, but pricing and shipping details remained incomplete.

• ›Step [1] (homepage) established Milbby as a Spanish arts & crafts retailer with 20,000+ products; the page title and meta description were the primary signals but did not expose deep structural information.
• ›Steps [2], [3], [4] revealed a critical navigation gap: standard URL paths (/pages/about, /pages/faq, /pages/pricing) all returned 404s, indicating either non-standard routing or missing pages. This forced reliance on web search (step [6]) rather than organic site discovery.
• ›Step [7] (/pages/asi-somos) successfully returned the About/Who We Are page, providing mission statement and community positioning; this was discovered only via search, not site navigation.
• ›Step [8] (FAQs page, found via search) was fetched but the response was truncated—specific FAQ content answering pricing and shipping questions was not visible in the agent's fetch.
• ›Step [9] (Club Milbby loyalty program) provided clear structural detail about the free loyalty offering, a key differentiator; this page was only accessible via search discovery.
• ›The site exposed product categories, employee count, store locations, and community mission, but withheld detailed pricing, shipping costs, and return policies—either behind non-fetched page sections or not published in machine-readable form.
• ›The agent had to assemble the final answer from fragments: product breadth from homepage meta, positioning from the About page, loyalty model from a dedicated page, and comparative differentiation from prior knowledge and inference rather than explicit competitor comparison on the site.