The agent assembled a partial understanding of delimenu by relying almost entirely on external sources—a GitHub repository and web search snippets—because the official website itself returned no meaningful content. The agent could infer the core offering (digital QR menus for restaurants, WhatsApp ordering, no commission model) but could not verify pricing, feature scope, or competitive differentiation from the site's own pages, forcing heavy reliance on inference and comparison articles.

• ›Step [1], [3], [4], [5], [18] all returned valid HTML from delimenu.co but contained only boilerplate Next.js structure with no readable content—the pages are client-side rendered and the agent could not extract text, tables, or structured data about features, pricing, or positioning.
• ›Steps [7] and [10] (web search and GitHub repo) were the only sources that yielded actual content: the GitHub README revealed the core mission ('digitalize menus, no physical contact') and the search result snippets described it as a free, zero-commission platform targeting restaurants, particularly in Spanish-speaking markets.
• ›The agent had to explicitly acknowledge major gaps: no public pricing information for the post-beta period, unclear monetization strategy, no visible documentation on integrations, analytics, or order management tooling—information that would normally live on a /pricing or /features page but was not accessible.
• ›The site's Spanish-only interface and lack of an English version, combined with dynamic rendering, made discovery harder; the agent resorted to six separate searches and found most answers in third-party comparison articles rather than delimenu's own documentation.
• ›The agent correctly cited only the GitHub repo and main homepage in sources, not the search results (which routed to content rather than delivering it), reflecting that the site itself published no agent-readable documentation—the final answer was mostly assembled from inference and competitive context.