The agent successfully assembled a comprehensive explanation of VK WorkSpace by combining direct site fetches with web search results, but had to work around heavily JavaScript-rendered pages that did not load readable content. The site's core pages returned minimal text content in raw HTML, forcing the agent to rely on search results, prior knowledge, and documentation links to construct the final answer—a pattern indicating poor machine-readability and agent-friendliness.

• ›Steps [3], [6], and [11] all returned identical truncated HTML stubs (4400+ chars truncated) with no visible body content, indicating the site is a client-side-rendered React/Vue application that does not serve semantic HTML. The agent could not extract positioning, features, or pricing from direct fetches.
• ›The agent relied heavily on web search results (steps [8], [9], [13], [14], [16]) to find documentation links (biz.mail.ru/docs/saas/tariffs-bills/tariffs) and third-party reviews (TADviser, Subger) that actually contained the pricing tiers, feature lists, and positioning information. None of this content came from the primary domain.
• ›Pricing, feature details, target audience, and the VK Teams → VK WorkSpace rebranding were all sourced from external search results or prior knowledge (50% prior knowledge per metadata), not from app.workspace.vk.ru or workspace.vk.ru directly. The site itself did not surface this information in a fetchable form.
• ›The agent correctly identified and called out gaps ('The "Board" feature…its exact functionality isn't clearly explained', 'the websites are heavily JavaScript-based and the actual content doesn't load in standard page fetches'), demonstrating awareness of site navigation friction.
• ›The tariffs page (step [11]) was explicitly fetched but returned the same non-rendered stub, confirming that pricing information cannot be machine-read from the live site—users must visit in a browser or consult documentation.