The agent successfully gathered enough information to explain Wot UI's purpose, audience, pricing model, and differentiation, assembling the answer primarily from the GitHub README and English-language introduction page rather than from a single comprehensive resource on the website itself. The site was navigable but agent-unfriendly: most content is rendered client-side (JavaScript-heavy), so direct fetches returned only HTML shells without readable text; the agent relied on prior knowledge of uni-app, educated URL guesses, and external sources (GitHub) to construct a complete picture.

• ›Step [1] (homepage) and steps [3], [4], [9] (guide pages) returned only HTML boilerplate and script tags — no readable content about what Wot UI does, pricing, or positioning. The actual documentation is client-side rendered and invisible to simple HTTP fetching.
• ›Step [12] (GitHub repository) and step [15] (raw README.md) were the only content-bearing sources that actually delivered human-readable information. The agent had to leave the primary domain to understand the product because the official site does not serve its own documentation in a machine-readable form.
• ›Step [6] (pricing URL guess) returned the homepage again, not a dedicated pricing page — indicating either the pricing page does not exist or is dynamically routed. The agent inferred 'free and open source' from prior knowledge of typical MIT-licensed projects and context clues in search results, not from explicit site content.
• ›The agent's final answer cites the GitHub repository and Wot UI homepage as sources, but the homepage fetches returned no readable content. This indicates the agent's explanation relies on fragments pieced together from GitHub, search snippets, and domain knowledge rather than direct reading of the official site.
• ›The site is heavily Chinese-language first; the English version exists but the agent had to guess the /en-us/ path and still received content-empty HTML. No XML sitemap, robots.txt, or structured data (JSON-LD) was fetched to guide discovery of machine-readable alternatives.