Agent successfully synthesized a coherent overview of EnemHub's business model, audience, and pricing strategy from the homepage and supplemented it with competitive context from an open-source alternative. However, the site's authentication wall prevented access to detailed pricing and documentation, forcing the agent to work around missing specifics and rely on homepage metadata to infer the offering.

• ›Step [1] homepage fetch was content-bearing: it returned the only comprehensive description of the service (80,000+ questions, API model, free-tier + paid tiers, cancelable subscriptions, São Paulo infrastructure). This single page supplied the bulk of the answer.
• ›Steps [2] and [3] (pricing and docs pages) both returned login walls rather than public content, revealing asymmetric information architecture — marketing claims visible to anonymous users, but detailed pricing/specs gated behind authentication.
• ›Step [4] (enemhub.com.br homepage) added context on the company's broader ecosystem (EnemHub Play is a separate free student product), but was not cited in final sources, suggesting the agent used it for orientation without relying on it for factual claims.
• ›Step [5] web search was cited and surfaced enem.dev as a direct competitor with published data (2,700 questions, free, open-source), allowing the agent to construct the differentiation table. Search snippet itself carried the competitor facts; the agent did not fetch enem.dev to populate this comparison.
• ›Step [7] (enem.dev fetch) confirmed competitor details but was used for context enrichment, not primary claims about platform.enemhub.com.br itself. The agent had to rely on model memory to infer EnemHub's advantages (scale, reliability, SLAs) by contrast rather than from explicit EnemHub positioning.