The agent assembled a comprehensive explanation of OpenFunnel by combining fragments from the official homepage, pricing page, and documentation site with content from a Y Combinator launch post. The main site itself was navigation-ready but sparse on product detail—the agent had to fetch external sources (YC launch, docs site) and rely on prior knowledge to construct a complete answer about what OpenFunnel does, who it's for, pricing, and differentiation.

• ›Step [0] (homepage) and [1] (pricing page) returned HTML but were not fully parsed in the trajectory—the agent indexed them but drew little explicit content from them; instead it pivoted to external sources for concrete details.
• ›Step [8] (Y Combinator launch post) was the single most content-bearing source, providing the core narrative: 'time-aware search engine,' the problem statement ('GTM search is broken'), and the key differentiator (signal-driven vs. database matching). This was not discoverable from the official site itself.
• ›Step [5] (docs.openfunnel.dev) was fetched but not deeply parsed; the agent acknowledged it as a resource for feature depth but did not extract specific content from it in the final answer, indicating the docs site exists but required deeper navigation than the agent performed.
• ›The official openfunnel.ai site does not publish structured positioning, pricing detail (credit amounts), or customer tier information in a machine-readable form—the agent had to infer these from fragmented HTML and external sources.
• ›The agent correctly identified what was *missing* from the site itself: specific credit-to-API-call mappings, tier comparisons, and direct positioning against alternatives. This shows low self-service machine-readiness for the discovery-evaluation intent.