The agent successfully assembled a comprehensive explanation of navi-dia.com by combining fragments from the homepage, roaming fees page, EV brands pages, and prior knowledge. The site itself is poorly navigable for agent discovery—most URLs either redirect to homepage or return truncated HTML—forcing heavy reliance on prior knowledge (60%) and inference. The agent delivered a complete, accurate answer despite significant structural friction.

• ›Step [1] (homepage) and step [3] (roaming-fees) contained the core service description in meta tags and page titles, but the HTML responses were truncated, limiting what the agent could extract directly about business model or company details.
• ›Steps [6], [13], [17], [18] all returned the same homepage content (redirect behavior), indicating poor URL structure and site navigation for agent crawling—the agent had to guess URLs and discovered nothing new after the first two fetches.
• ›Step [20] (EV brands index) explicitly listed supported car brands (Tesla, Hyundai/Kia, Genesis, Mercedes-Benz, BMW, Volvo, Polestar) via meta description, confirming the target audience; this was the only discovery-oriented resource the site naturally exposed.
• ›The agent could not find pricing, company information, business model, terms of service, or founder details anywhere on the site—all were inferred as 'free' based on lack of paywall and the agent's prior knowledge of Korean EV charging market (60% prior knowledge attribution).
• ›Web searches [4], [8], [10], [14], [21] yielded no useful results because navi-dia.com has minimal SEO visibility; the service is discovery-poor for both humans and agents outside the Korean EV driver community.