The agent successfully assembled a comprehensive explanation of JOJO Zoo Park by combining direct site fetches with web search results, covering what the park does, its target audience, pricing, and differentiation from competitors. The official website provided metadata and navigation structure but most detailed content required supplementary web search; the agent worked around incomplete HTML captures by referencing external travel blogs and guides to fill gaps on operations, features, and audience positioning.

• ›Step [1] homepage fetch and steps [3], [4], [7] (ticket and about pages) provided core identity information via meta descriptions and page titles, but the actual HTML body content was truncated, forcing reliance on external sources for details like specific animal species, facility names, and full pricing tiers.
• ›Steps [6], [10], [11], [12] (web searches) proved essential: search results cited official pages (jojozoopark.com/ticketdesc) and travel blogs that contained the specific pricing (NT$560), animal types, zone count, founder investment story, and competitive positioning versus Taipei Zoo—information the agent could not extract directly from the official site's incomplete fetches.
• ›The site is agent-hostile in execution: it is entirely Traditional Chinese, WordPress-based with truncated HTML responses, lacks a detailed species/attraction directory accessible via direct URL paths (evidenced by 404s on /attractions and /animals), and does not publish structured data (JSON-LD, schema.org) that would surface key facts like hours, full pricing, or animal roster to an LLM without supplementary search.
• ›The agent had to guess URL patterns (/attractions, /animals) and rely on 50% prior knowledge + 33% previous artifact + 17% web search to compensate for the site's poor machine-readability; most actionable details (bumper cars, dinosaur train, carousel, family combo pricing, zero-distance interaction model) came from third-party travel guides, not the official site.