The agent was unable to access questoapp.com directly due to Vercel security blocking all pages (429 errors on steps 1, 6, 7, 8), and instead assembled a comprehensive explanation of Questo from web search results and app store listings. The final response covers what Questo does, who it's for, pricing models, and differentiation from competitors, but lacks specific pass prices and exact cost breakdowns because the pricing pages themselves remained inaccessible. The site is poorly navigable for agent access; critical information exists but is behind a security checkpoint.

• ›All direct fetches to questoapp.com returned 429 Vercel security blocks; the agent could not read the actual website content despite multiple attempts at different URLs (/about, /faq, /passes, /creator-room).
• ›Web search results (steps 3, 4, 10, 11, 13) supplied URL references to pricing and FAQ pages, but the search snippets themselves contained only metadata titles and descriptions, not the actual content. The agent had to infer Questo's business model and pricing structure from the app store listing and search result titles rather than from authoritative site content.
• ›The agent successfully triangulated core product information (gameplay mechanics, pass-based model, 1000+ cities, creator economy) from indirect sources (Google Play store, Product Hunt competitor comparisons, blog references in search results), but could not verify specific prices, currency handling, or detailed revenue splits that would be on the /passes and /creator-room pages.
• ›The site publishes URLs and claims about itself (e.g., 'Questo Passes, Unlimited Walking Tours & City Exploration') in search indexing, but the actual content behind those URLs is not machine-accessible due to Vercel's security layer, making the site effectively opaque to agent-driven discovery of pricing and policy details.
• ›The agent acknowledged gaps in its final response (specific pass pricing, exact cost breakdowns, monetization clarity, offline capabilities) and was transparent about sourcing 75% from web search and prior knowledge—indicating low confidence in accuracy on price-sensitive claims.