The agent successfully assembled a comprehensive explanation of Sandals Resorts by combining sparse on-site content with third-party travel guides and blog posts. The website itself was minimally navigable for structured product understanding—key pages like homepage, resorts listing, all-inclusive details, and blog existed but returned truncated HTML that didn't surface pricing, room categories, or what's-included details in machine-readable form. The agent had to rely heavily on web search results and external sources to fill critical gaps, particularly for pricing, room tiers, and competitive differentiation.

• ›Steps [1], [3], [6], [7], [10] fetched core Sandals pages but returned only HTML structure fragments (truncated at 4400 chars), providing minimal extractable content about what the company does, pricing, or inclusions. The agent could not read substantive product information from the site itself.
• ›Steps [12], [17], [20] (web searches) were the primary source of detailed, citable facts: pricing ranges ($250–$280/person/night), room category tiers (Luxury/Club/Butler), what's included (16 restaurants, unlimited scuba, water sports), and competitive comparisons vs. Secrets. These third-party travel guides contained more structured product data than the official site.
• ›Step [15] (/all-inclusive/what-is-included) returned 200 but truncated response; agent could not verify actual inclusions from this URL directly and relied instead on search results citing the same page.
• ›Step [18] (blog) returned readable HTML but required external search [step 20] to locate the specific blog article on room categories cited in the final response.
• ›The site lacks clear pricing display, booking flow visibility, and structured data markup that would expose room types, inclusions, or rate tables to automated agents. No FAQ, comparison table, or machine-readable schema was discovered.
• ›Agent successfully bridged gaps using prior knowledge (50%) and search (40%), assembling a coherent narrative despite the site's limited machine-readability. The task required synthesis rather than single-source lookup.