The agent successfully assembled a comprehensive explanation of Promiedos by combining web search results, partial site fetches, and prior knowledge about Argentine football. The site itself was minimally cooperative—initial direct access timed out, and subsequent HTML fetches returned only boilerplate structure without semantic content. The agent relied heavily on search snippets, external references (Google Play store, case studies, user reviews), and inference to answer the task, ultimately delivering a coherent answer despite the site's poor machine-readability.

• ›The site's homepage fetch [5] returned only HTML boilerplate with no structured data or meta-content that clearly explained purpose, pricing, or differentiation—the agent had to infer these from search results and external sources.
• ›Search results [3, 7, 8, 17, 23, 24, 26] and their snippets were the primary source of factual claims (free platform, Argentine football focus, 'promedio' system, available on Google Play). The site itself did not publish this information in a directly fetchable form.
• ›External references (Google Play store [10], case study [21], user review sites [18]) provided more actionable context than the site's own pages, indicating Promiedos relies on third-party platforms for discoverability and explanation rather than self-documenting.
• ›The agent correctly identified the 'promedio' (average standings) as the key differentiator only through targeted search queries [24, 26] about Argentine football systems—this insight was not exposed on the site itself.
• ›Pricing information (free, ad-supported) was inferred from the absence of pricing pages and the app listing, not stated explicitly on the site.
• ›The site's poor availability (timeouts, lack of semantic structure) forced the agent to operate in a 'heavy bridge' mode, assembling answers from external fragments rather than direct site exploration.