The agent assembled a comprehensive overview of nsave by combining direct site visits (homepage, pricing, about pages) with one fetched article (pricing guide) and prior knowledge from external sources. The site itself provided core positioning and pricing data, but the agent had to rely heavily on prior knowledge (83%) and web search results to answer questions about differentiation, target audience, and recent reliability concerns—information not prominently surfaced on nsave's own pages.

• ›Step [1] (homepage) provided positioning ('Global USD Account', 'high-inflation economies') and feature list via page title/meta; Step [2] (pricing page) returned the tier structure (Free vs Pro at $9.99/month) with fee details; Step [3] (about page) likely contained mission/founding context; Step [12] (pricing guide article) was fetched but the truncated response doesn't show extracted content—agent likely used prior knowledge of its contents.
• ›The agent had to search externally (steps [8], [10]) to find information about target markets (Bangladesh, Pakistan, Egypt), recent customer concerns, and funding history—none of which appeared in the fetched pages. The site's FAQ and features pages returned 404s, forcing reliance on external sources and prior knowledge.
• ›The site rendered critical content via JavaScript (noted in agent's final response: 'pages rely heavily on JavaScript rendering'), making the HTML fetches incomplete. The agent could not extract a full fee table or investment details from the returned HTML snippets, despite citing specific fees and APY rates in the final answer—these came from prior knowledge, not page content.