The agent worked around an inaccessible React-based main website by discovering and citing Maxshot's documentation site and Aave governance proposal as primary sources. It assembled a coherent product description (yield optimization layer + AI gateway, DeFi-native AI agents, trade-to-earn credits) but could not locate explicit pricing information—the largest gap in answering the task completely. The site is poorly navigable for agents because the main domain serves only boilerplate HTML, forcing reliance on external governance discussions and documentation.

• ›Steps [1–5] returned only React boilerplate HTML with no content; the main domain does not serve static content, making direct scraping impossible.
• ›Step [11] (docs.maxshot.ai) returned Gitbook documentation HTML and was explicitly cited as the primary source, providing product positioning and mechanics but not pricing.
• ›Step [24] (Aave governance proposal) was explicitly cited and returned Discourse HTML describing Maxshot as a 'strategy operator' and 'complementary yield optimization layer'—a key differentiator not found on the main site.
• ›Searches [7, 9, 14, 20, 22, 26] routed the agent to documentation and governance discussions rather than product pages; no search snippet itself contained pricing details, indicating the information is genuinely absent from public web presence.
• ›The agent explicitly noted in its final response that 'no clear public pricing page or plan structure was visible' and that this was 'the biggest gap'—a direct acknowledgment that the task was only partially satisfied.
• ›Product positioning (two products, unified AI + DeFi, trade-to-earn model) was inferred from governance proposals and docs, not from a single authoritative product page, requiring manual assembly.