Agent successfully assembled a comprehensive overview of Semestra from repeated fetches of the landing page, which bundled product description, pricing, features, and FAQ into a single page. The site is agent-readable but required multiple passes and model reasoning to synthesize fragmented information; it does not publish competitor comparisons or company background.

• ›All four fetches returned the same URL (semestra.com.br/) with complete product information bundled into the landing page—no separate feature, pricing, or about pages. Agent had to synthesize across four passes of the same content, suggesting the site is heavily single-page but content-rich enough for extraction.
• ›The site explicitly addresses common objections (no credit card required, no auto-charges, data export, read-only access post-cancellation) in FAQ and pricing sections, making trust and transparency positioning directly fetchable and substantive.
• ›No competitor mentions or comparisons appear in any fetched response. Agent noted this gap but correctly attributed it to site absence rather than failed discovery—the site simply does not position Semestra relative to alternatives.
• ›Core product facts (features, pricing, target audience, onboarding philosophy) are all present and directly cited in step responses. The agent's final 'What I Couldn't Find' section relies on model knowledge of common SaaS information gaps, not site retrieval failures.
• ›Site uses descriptive Portuguese labels (MAT, CAL, REV, SEM, R$) for feature modules. Agent correctly decoded and translated these without fetching a dedicated glossary—the context and labels themselves carry meaning.