The agent successfully assembled a comprehensive explanation of Cerdanyola Activa by combining web search results with site fetches, though the website itself was poorly structured and required heavy reliance on search engine snippets and prior knowledge. The site's dynamic rendering and lack of clear navigation made it difficult to extract definitive information about pricing, service scope, and eligibility — forcing the agent to infer answers from fragments and acknowledge gaps in the final response.

• ›The agent retrieved raw HTML responses from multiple site pages (steps 2, 5, 6, 11, 12) but the fetched content was minimally informative due to heavy JavaScript rendering and boilerplate code — the actual page content was not visible in the raw response. The agent relied on search results (steps 8, 9, 14, 15, 17, 18, 20) to surface human-readable snippets about services, not on parsing the fetches themselves.
• ›Web search results provided the actionable discovery layer: search snippets revealed that Cerdanyola Activa offers employment, entrepreneurship, business advisory, and networking services. The site's own URL structure (/emprenedoria, /preus, /qui-som, /assesorament-a-empreses, /treball) indicated these service categories, but the agent had to guess these paths rather than following an explicit sitemap or navigation menu visible in the fetches.
• ›The agent explicitly flagged missing information in its response — no clear pricing page, vague service scope, unclear eligibility criteria, and limited English content — indicating the site does not publish essential information in a machine-readable or accessible form. The agent filled gaps using contextual inference (inferring free/subsidized services from 'municipal' status and search hints like 'gratuito') rather than direct sources.