The agent successfully gathered enough information to explain Oso's core offering, pricing tiers, and differentiation, though it had to work around incomplete fetches and fragmented content. The homepage, pricing page, product page, and learn section provided the main narrative; docs were less helpful for high-level positioning. The site's structure made discovery possible but required the agent to synthesize from multiple pages and acknowledge gaps (pricing details cut off, unclear product boundaries between Oso Cloud and Oso for Agents).

• ›Step [1] (homepage) and [4] (product page) returned meta descriptions and title tags that clearly framed Oso for Agents as an 'AI Agent Security & Control Platform' with 'monitoring, access controls, and automated least privilege' — this formed the core positioning without needing to parse full HTML.
• ›Step [3] (pricing page) was fetched but responses were truncated; the agent inferred pricing tiers (Developer free, Growth $15/user/month, Enterprise custom) but explicitly noted it could not see full enterprise details — a gap in the site's agent-readiness.
• ›Step [11] (oso-for-agents page) and [15] (learn section) provided differentiation context, but the agent had to assemble the comparison framework (least privilege, behavioral controls, authorization-first) from truncated HTML and prior knowledge rather than from a dedicated 'vs. competitors' resource.
• ›The site's information architecture split Oso Cloud (general authorization) and Oso for Agents (AI agents) into separate sections; the agent correctly identified this ambiguity as confusing but could not definitively resolve which features belonged to which product from the fetched pages.
• ›Web searches (steps [7], [8], [12], [14], [17], [18]) were primarily routing tools pointing to pages already fetched; none of the search results themselves contained new answer content, indicating the site's own pages were the source of truth but not optimally structured for agent parsing.