Agent successfully assembled a comprehensive overview of VocataWeb's positioning, services, and pricing by repeatedly fetching the homepage (all steps reused the same URL). The site's lack of dedicated subpages forced the agent to extract information from a single resource, which it did effectively but required the agent to recognize and flag gaps—particularly around AI service specificity and pricing transparency—that the site itself did not clarify.

• ›All four content-bearing steps fetched the same URL (vocata.dk/) typed from memory, not discovered via site navigation—the site appears to have no internal navigation, subpages, or menu structure, so the agent could not follow links to distinct pricing, services, or about pages. The 75% 'followed a link' metric in the metadata is misleading; all substance came from one fetch repeated for clarity.
• ›The site publishes core facts (services, pricing philosophy, client ownership, free mockup promise) in narrative form on the homepage, not as structured data, case studies, or dedicated resource pages. The agent had to recognize and extract these facts from prose.
• ›Pricing information was present but deliberately vague: the site states a principle (10-20% below market) and a process (custom quotes after mockup) but no actual rates, project examples, or cost ranges. The agent correctly flagged this as a gap but could not retrieve more without contacting the business.
• ›AI services ('AI visibility' for ChatGPT/Claude/Copilot discovery) were mentioned but not explained; the agent inferred what these might mean but explicitly noted the uncertainty in its 'confusing points' section, indicating model judgment rather than retrieved clarity.
• ›The site is highly agent-hostile for discovery-evaluation tasks: no pricing table, no comparison matrix, no FAQ, no service menu, no case study index. The agent succeeded by extracting and synthesizing fragments from a single prose homepage, but had to openly acknowledge missing details rather than pretend completeness.