The agent successfully assembled a comprehensive explanation of Mobbin by combining direct site fetches (homepage, pricing, about pages) with third-party review and alternative-comparison sources, since Mobbin's own pages are JavaScript-heavy and text-hostile. The final answer covers what Mobbin does, its audience, pricing tiers, and competitive differentiation—but pricing specifics remain approximate because the native /pricing page did not render readable text, forcing reliance on third-party pricing aggregators and review sites.

• ›Steps [1], [2], [3] (homepage, pricing, about) were fetched but returned Framer/Next.js boilerplate with minimal readable text—the agent noted this friction and pivoted to web search and third-party sources.
• ›Steps [11], [14], [15] (Vendr, TechJockey, UX Magic) provided the actual substantive content: Vendr contributed pricing structure details, TechJockey and UX Magic supplied feature comparisons, audience segmentation, and competitive positioning that the agent could not extract from Mobbin's native site.
• ›The agent explicitly cited all six steps in its final sources list, confirming they were the primary content-bearing resources; the native site was used for credibility and framing, but third-party sources filled most of the information gaps.
• ›Mobbin's site architecture (JavaScript-rendered, Framer-based) made direct scraping impractical; the agent had no access to machine-readable structured data (no schema markup, API, or llms.txt detected), forcing heavy reliance on search + aggregator sites.
• ›Key details like '2.3M+ users', '600,000+ screens', pricing tiers ($10–15/month Pro, $16–40/seat Team), and competitor names all came from third-party sources, not from Mobbin's own published content.