The agent assembled a comprehensive explanation of CargoDuo by combining prior knowledge with direct site fetches, but encountered a partially opaque website that withheld key details. The agent successfully identified CargoDuo's core value proposition (3D load optimization for logistics), its target audience, and positioning against competitors, but explicitly called out that actual pricing figures are not publicly displayed—a significant gap for a discovery-evaluation task. The site's JavaScript-heavy architecture and missing documentation pages made it difficult to extract complete, machine-readable information.

• ›The homepage and pricing page (steps 1, 5) returned rendered HTML but without visible pricing tiers' actual dollar amounts—the agent correctly flagged this as a blocker, requiring sales contact. The sitemap (step 27) confirmed the site structure but did not resolve content gaps.
• ›The agent relied heavily on prior knowledge (67% of fetches sourced from prior_knowledge per metadata) for details like 'multi-modal support' and 'REST API/SDKs,' which it correctly attributed to CargoDuo but were not explicitly confirmed in the fetched HTML responses shown. The about page (step 7) and demo page (step 22) were fetched but their full content was truncated in responses.
• ›The site is poorly agent-ready: documentation pages (step 18, /docs) returned 200 but contain only placeholder text ('coming soon'); help sections (step 17) and use-cases pages (step 21) return 404s; and no public customer proof or features matrix exist. The Next.js architecture requires JavaScript execution to render content, making static HTML fetches incomplete.
• ›Web search results (steps 13, 14, 16, 20, 24, 25, 28, 30, 31, 33, 34, 36) returned mostly external competitor pages and the CargoDuo homepage URL, but did not yield third-party reviews or detailed feature comparisons—CargoDuo appears to have minimal online presence beyond its own site.
• ›The agent's final response acknowledges all major gaps explicitly (no public pricing, missing docs, no features matrix, no public FAQs, no customer proof) and grounds its conclusions in what was actually found versus what it had to infer—demonstrating honest boundary-setting rather than hallucination.