The agent successfully assembled a comprehensive explanation of Realm Interactive by combining fragments from the official website (homepage, about, games, blog) with Steam store pages and web search results. The site's HTML was truncated in responses, forcing the agent to rely heavily on web search and prior knowledge to piece together what they do, pricing, and positioning; critical details like DLC pricing and release dates remained unavailable on the official site itself, revealing gaps in information architecture.

• ›The official website pages (steps [1], [3], [4], [15]) returned truncated HTML that did not render the actual content—the agent could not extract text from realminteractive.com directly and instead relied on search results and Steam store pages to construct the answer.
• ›Steam store pages ([8], [10]) and web search results ([6], [7], [14]) became the primary content sources; the agent found no dedicated pricing page on the official website and had to note this as a gap. Blog post ([15]) was discovered via site-specific search but also returned truncated content.
• ›Agent-readiness is low: the site's Next.js rendering means the agent cannot parse the HTML statically. Critical business information (pricing, release timeline, game roadmap, contact info) is either missing from the official site or locked behind client-side rendering, forcing the agent to use web search and Steam as proxies for truth.
• ›The agent correctly identified itself as having used prior knowledge (17%), web search (50%), and previous artifacts (33%)—the web search component was essential to answer the task, indicating the official site alone is insufficient for discovery and evaluation.