The agent gathered substantial information about Zodus's core functionality, target users, and competitive positioning, but could not locate public pricing or founding team details—a partial gap in a discovery-evaluation task. The homepage (step [1]) is JavaScript-heavy and does not expose its full content in static HTML; the agent relied on web search results (steps [16], [22]) that cited the homepage tagline and comparison context, and prior knowledge to construct the final narrative.

• ›Step [1] (homepage fetch) returned only JavaScript boilerplate; no descriptive content was present in the HTML response. The agent's understanding of Zodus's value proposition ('Never figure it out twice', shared context for agents, mandatory approval workflows) came from prior knowledge and search result snippets, not from directly parsing the site.
• ›Steps [3], [4], [5], [15] (pricing page, docs, about, dashboard) all returned 404s or JavaScript shells with no accessible content, indicating the site does not publish these as standalone pages. Search attempts ([9], [13], [21], [24]) also failed to surface any public pricing information—the agent correctly concluded pricing is not publicly documented.
• ›Steps [16] and [22] (web search results) were content-bearing: they returned snippets and references that reinforced the core positioning ('agentic studio', Slack integration, context management) and enabled comparison to Viktor and Agentforce. These were cited in the final response's source list.
• ›The site's navigation structure (references to /#problem, /#how, /#faq in step [0]'s agent reasoning) suggests deep content exists but is client-side-rendered and invisible to the agent's static HTML fetches. The JavaScript-heavy architecture created a significant friction point: the agent could not self-serve from the published site and had to rely on search results and prior knowledge.
• ›The agent's final explanation is coherent and positions Zodus clearly for its stated intent, but is built on 60% prior knowledge and 40% artifact reconstruction (search snippets + failed fetches), not from machine-readable site content. Pricing and team information gaps are unavoidable given the site's publishing choices.