The agent successfully gathered enough information to explain DEWA's core function, pricing structure, and market position. However, the site itself was not the primary source—the agent relied heavily on web search results and Wikipedia to extract concrete details like tariff rates, fee breakdowns, and service offerings. The official DEWA pages were JavaScript-heavy and returned truncated HTML that didn't expose the actual content, forcing the agent to work around the site's technical limitations by pulling from third-party sources and prior knowledge.

• ›Steps [2], [7], [8] fetched official DEWA pages but returned only truncated HTML (4400 char limit, no visible content in responses). The agent could not extract pricing, services, or positioning from the official site's raw content.
• ›Step [5] search for pricing returned links to tariff pages, but the agent still had to infer the actual rates (0.23–0.38 AED/kWh) from external sources like third-party tariff explainers rather than from DEWA's own fetched pages.
• ›Step [9] and [11] (Wikipedia) and the broader web search results (steps [5], [10]) became the primary content-bearing sources—they provided the structured explanation of DEWA's monopoly status, service model, and how it differs from competitors. The official site did not surface this positioning.
• ›The agent had to assemble the final answer from fragments: tariff calculator links from DEWA's site, rate details from external tariff trackers, and competitive context from Wikipedia—no single DEWA page delivered the full picture.
• ›86% of fetches were sourced from web search, indicating the site's own pages were not sufficiently machine-readable or content-rich to answer the task directly.