The agent successfully assembled a comprehensive overview of ChickyTutor by combining the homepage fetch with blog comparison pages and third-party review aggregators, since the site's navigation structure (missing /pricing, /about, /features pages) forced reliance on web search and external sources. The final answer covers what ChickyTutor does, who it's for, basic pricing (€15/month), and competitive positioning, though several specifics (exact free vs. paid feature boundaries, multiple tier existence, app/web format) remained unclear because the site does not publish detailed pricing or feature documentation in a machine-readable or easily discoverable form.

• ›Step [1] (homepage) returned Next.js-rendered HTML that did not expose pricing, features, or positioning in the response body — the agent had to infer these from blog content and comparison pages instead.
• ›Steps [10], [11], [12] (blog posts vs-loora, vs-italki, schools) and [17], [18] (Uneed and AIpure review aggregators) provided the most actionable content, revealing that ChickyTutor positions itself against specific competitors and offers a schools/corporate tier, but these pages were discovered via web search, not site navigation.
• ›Traditional site paths (/pricing, /about, /features) all returned 404 errors, forcing the agent to rely on 56% web search + 33% cached/prior artifacts to answer a discovery-evaluation task, indicating poor information architecture for AI navigation.
• ›No structured data (JSON-LD, microdata) or pricing schema was visible in any fetched response, and the site does not appear to publish a pricing page, feature list, or terms in a canonical, machine-readable location.
• ›The agent explicitly noted confusion on 5 key points (feature breakdown, multiple tiers, implementation details, app vs. web, enterprise pricing), all of which stem from the site's lack of published documentation, requiring the agent to fill gaps with educated guesses and third-party sources.