The agent successfully assembled a comprehensive explanation of probabilitysurvey.com by combining limited on-site content (homepage, results page, humans-vs-AI page) with external research. The site itself is minimal and does not publish structured metadata, an about page, or pricing information — the agent had to rely on GitHub discovery, HBR article, and academic references to answer the full brief. Despite the site's narrowness, the agent delivered a satisfying explanation of what the product does, who it's for, pricing (free), and differentiation.

• ›Step [3] (homepage) and Step [5] (humans-vs-AI page) returned only client-side JavaScript bundles with minimal visible HTML content; the agent could not extract structured answers from the site itself and had to infer purpose from URL structure and search context.
• ›Steps [14] and [15] (GitHub repository discovery via web search) proved critical: the GitHub link revealed the creator as Andrew Mauboussin and provided source code context, but the repository README was inaccessible (404 in step [16]), forcing reliance on external blog posts and HBR article (step [18]) to establish credibility and research lineage.
• ›Step [13] (University of Illinois visualization by Wade Fagen-Ulmschneider) and Step [18] (HBR article on Mauboussin's probability language research) supplied the historical context and business case that the site itself does not articulate; the site lacks an explicit 'About' or mission statement page.
• ›The site is extremely minimal (3 pages, client-side rendered, no docs, no API), requiring the agent to supplement on-site navigation with external search to fully answer the discovery-evaluation task; on-site discoverability of authorship and purpose is very low.