The agent successfully built a comprehensive understanding of Tiltiden by assembling information from sparse official pages, a sitemap, and web search results. The site itself publishes minimal information—pricing and features pages exist but return only boilerplate HTML with no visible content—forcing the agent to rely heavily on prior knowledge and search results to answer the task. The agent delivered a well-structured explanation of what Tiltiden does, who it's for, pricing, and differentiation, but had to work around the site's thin public information.

• ›The sitemap [24] revealed the site structure (priser, funktioner, bookingsystem-til pages) but the actual feature and pricing pages [3, 27, 28] returned only HTML skeletons with no visible text content—the agent could not extract details from the pages themselves.
• ›Web search results [11, 17, 20, 22] surfaced a guide on payment processing and the structure of industry-specific pages, but these were only discovered via search, not from the site's navigation or information architecture.
• ›The agent correctly identified that the site is minimal and sparse—no About Us, no customer testimonials, no detailed feature comparisons are publicly visible. The homepage and main pages offer almost no indexable content to crawlers or users.
• ›Pricing and core positioning had to be inferred from the sitemap structure and search results rather than from readable page content. The agent's final answer is heavily reliant on prior knowledge (45% per metadata) and web search (18%), not on the site's own content.
• ›The site's use of modern JavaScript rendering (Next.js) meant that structured content, if it exists in the DOM, was not rendered in the HTML responses fetched—this severely limited what the agent could extract from direct page fetches.