The agent partially satisfied the task by assembling a coherent overview of Exapuni from web search fragments and social media references, but the website itself was largely inaccessible—the homepage and course pages returned JavaScript-heavy HTML that didn't expose meaningful content. The agent relied heavily on search results and prior knowledge to describe what Exapuni does (video courses for Argentine university students), who it's for (CBC and UBA XXI students), and how it differs from competitors, but explicitly flagged that pricing information was conflicting and the site's publicly accessible pricing page returns a 404. The site's heavy reliance on JavaScript and lack of a clear pricing structure made it difficult to extract complete, authoritative information directly from the domain.

• ›Steps [1], [2], [9] fetched the homepage and course pages but returned only boilerplate HTML (Google Tag Manager scripts, truncated response bodies) with no visible course listings, pricing details, or feature descriptions—the actual content is likely rendered client-side and unavailable to the agent.
• ›The agent's understanding of Exapuni's core offering (video lectures, exercise guides, exam models, ExaComunidad, ExaBoti) came primarily from web search result snippets (steps [4], [5], [7], [8], [10], [11]) and prior knowledge (40% of fetches), not from the website itself. The domain was cited in sources but not because it contained that information.
• ›Step [3] attempted to fetch `/precios` (pricing) and received a 404 error, confirming that pricing information is not publicly accessible or discoverable through standard URL guessing. Step [12]'s pricing search returned conflicting figures ($1,499, $17,000, $39,000 ARS) from third-party sites, not from exapuni.com itself.
• ›Step [14]'s search for 'about us' and team information returned no substantive results—the company maintains social media presence (Instagram, Facebook, YouTube, Twitter) but does not publish founder information, mission statement, or organizational details in a fetchable format.
• ›The agent had to work around the site's inaccessibility by relying on search engines and social media presence to infer positioning and differentiation (ExaComunidad and ExaBoti features). No structured data, schema markup, or open API documentation was discovered.
• ›The site is JavaScript-heavy and not agent-friendly; content that would satisfy the task (pricing, course catalog, team/mission, feature comparison) either doesn't exist in public form or is behind authentication/client-side rendering.