The agent gathered a solid high-level understanding of Tango's purpose, target audience, and differentiation by combining direct site fetches with prior knowledge, but could not complete the pricing breakdown requested — the pricing page HTML was truncated and did not render readable tier/cost details. The site is reasonably navigable for discovery but lacks machine-readable pricing structure on the main pages accessed.

• ›Steps [0] and [5] (homepage and main marketing site) contained clear value propositions and feature lists via HTML that revealed Tango consolidates 8+ federal data sources into one API; step [4] (FAQ) reinforced use cases and target personas without directly citing it, suggesting the agent inferred from accumulated context.
• ›Step [1] (pricing page) was fetched but the HTML response was truncated, leaving specific pricing tiers, costs, and plan feature matrices inaccessible — the agent could not extract the exact information the task required and explicitly acknowledged this gap.
• ›The agent relied heavily on prior knowledge and web search (60% combined) to construct the 'how it's different' narrative and token-efficiency comparison ($9,400 vs $3,600 claim), rather than extracting these from the fetched pages themselves, indicating the marketing site does not prominently publish direct competitor cost comparisons or technical efficiency metrics in machine-readable form.
• ›The site structure is discoverable (pricing and FAQ links present) but not optimized for agent data extraction — pricing details, rate limits, and SLA guarantees exist but were not surfaced in the fetches, requiring the agent to call out what it could not find rather than synthesize a complete answer.