The agent successfully assembled a comprehensive understanding of Sui by combining fragments from the main site, developers page, documentation subdomain, and blog—supplemented heavily by prior knowledge and web search results. The site itself is poorly agent-navigable: key pages like /pricing returned 404s, main content relies on JavaScript rendering that obscures raw HTML, and core value propositions ("Sui Stack," object-centric design, AI-native features) are scattered across multiple subdomains without clear, machine-readable explanation. The agent had to compensate by inferring structure and relying on external sources.

• ›Steps [1], [2], [6], [12] returned HTML with minimal extractable content due to JavaScript-heavy rendering; the agent obtained actual product understanding from web search results and prior knowledge (57% of sources), not from fetched site content.
• ›Critical resources like /pricing returned 404, forcing the agent to discover gas fee information via web search rather than official documentation. The site does not publish pricing in a discoverable location, which is architecturally correct (Sui is a blockchain, not a SaaS product) but created navigation friction.
• ›Step [7] (docs.sui.io) and step [12] (blog.sui.io) were cited in the final response, but the raw HTML responses shown in the trajectory contain no extractable text—indicating the agent relied on prior knowledge of what these resources contain rather than parsing the actual fetched content.
• ›The agent explicitly surfaced confusion about the "Sui Stack" concept and the object-centric data model, indicating these core differentiators are not clearly explained on the primary site—the agent had to synthesize understanding from multiple external sources (Messari, DexTools, KuCoin Learn).
• ›29% of sources came from previous artifacts, suggesting the agent drew on cached knowledge about Sui rather than discovering it fresh from the site structure.