The agent successfully assembled a coherent picture of REACT!V's business model, target audience, and positioning from partial page content and WordPress API responses, but could not find publicly available pricing information despite multiple targeted attempts. The site's content is fragmented across HTML head metadata and WordPress endpoints rather than in readable page bodies, making it navigable only through prior knowledge and API access rather than through normal web browsing.

• ›Steps [1], [3], [6], [11], [15] returned truncated HTML where actual content was cut off mid-render; the agent relied on meta descriptions, page titles, and script comments to infer what the pages contained (e.g., learning the company is infrastructure-focused from the comment 'REACT!V — purga de los identificadores que dejó la analítica retirada').
• ›Step [9] and [16] (WordPress REST API endpoints) were the only sources that returned complete, machine-readable structured data—the agent discovered these by educated guessing and used them to identify blog posts about 'LLM routers' and operational topics, which informed the inference that REACT!V is a technical consulting firm.
• ›The agent found NO pricing data anywhere on the site—no /precios, /pricing, or /planes pages exist (step [5] returned 404); this gap was explicitly called out in the final response as a major limitation, suggesting the site deliberately hides pricing behind custom quotes.
• ›The site is not agent-friendly: pages load as rendered HTML with truncated body content, requiring either JavaScript rendering or CSS parsing to see full text. The WordPress API was the only reliable source of complete information, suggesting the site may not be optimized for bot access.
• ›The agent backfilled missing information using prior knowledge (stated as 50% sourced from 'prior knowledge') to construct a coherent narrative, inferring the company's focus from blog post slugs, meta text, and the 'Contacto' page description rather than from explicit positioning statements.