The agent assembled a working explanation of itinservices.com by combining prior knowledge, web search snippets, and a successful fetch of their Shopify shop, but the site's main domain was largely inaccessible—most internal pages returned 404s, forcing the agent to rely on search results and inferred information rather than directly surfaced content. Despite this friction, the agent delivered a reasonably complete answer about what they do, who it's for, pricing, and how they compare to competitors.

• ›Step [1] (homepage fetch) returned a Next.js application but the response was truncated and the agent could not extract usable content from the dynamic HTML; no pricing, features, or process information was accessible from the main domain.
• ›Steps [3, 4, 6, 7, 12] all returned 404 errors (/pricing, /how-it-works, /about, /faq, /features), indicating either a site structure problem or that these pages do not exist—a critical friction point for a discovery task.
• ›Step [8] (shop.itinservices.com) successfully returned a Shopify store homepage, confirming they have a shop presence, but provided no actionable detail about services or pricing.
• ›Steps [10, 15, 18] (web searches) were the primary source of substantive information: search snippets and linked pages (including doc.itinservices.com in step [13]) revealed pricing ($160–$170), CAA status, target audience, and competitor comparisons that the agent's own site navigation could not uncover.
• ›Step [13] (doc.itinservices.com help center) was successfully fetched but the response was truncated; the agent cited no specific content from it, suggesting it was exploratory rather than content-bearing.
• ›The agent had to lean on prior knowledge and external search results to construct most of the final answer—pricing, process details, and market positioning came from web search, not from itinservices.com's own pages.
• ›The site exhibits poor discoverability for an agent: key pages return 404s, the homepage is a dynamic Next.js app with truncated content, and critical information (pricing, features, how-it-works) is not directly published in a machine-readable or easily fetchable form.