The agent assembled a partial but substantive understanding of PasseJá by combining fetches from the live site (homepage, help page, about page, test generator) with web search results and app store listings. It successfully identified what PasseJá does (AI homework solver for students), who it's for (Brazilian students), and how it differs from competitors (more generalist than Photomath, AI-focused vs. Brainly's human model). However, the site's JavaScript-heavy single-page architecture prevented direct access to pricing details, forcing the agent to rely on prior knowledge and search inference to partially address the pricing question. The site exposed minimal machine-readable information about plans or cost.

• ›Step [1] (homepage) returned only HTML scaffolding with no readable content—typical of Next.js SPA apps—leaving core information inaccessible to direct fetch. The agent had to infer features and positioning from search results and app store listings instead.
• ›Steps [21], [22], and [30] (about, simulados, ajuda pages) all returned identical empty HTML shells, indicating the entire site uses client-side rendering that doesn't populate during server-side fetching. These pages are navigable by URL but not content-bearing.
• ›Step [16] (Chrome Web Store) and steps [7], [8], [14], [18], [25] (web searches) provided the only substantive content: app store descriptions, competitive comparisons, and third-party reviews filled the gap that the official site could not.
• ›The agent found free tier (3 questions/day) and premium tier existence through search, but exact pricing remains absent from both the official site and indexed search results, indicating PasseJá does not publicly surface pricing in a machine-readable or even human-readable indexed form.
• ›The site is discoverable (via search and app stores) and the core positioning is inferrable from auxiliary sources, but the official site itself is opaque to both humans and agents trying to read it directly.