The agent successfully assembled a comprehensive explanation of Meko by combining external third-party coverage (Yugabyte blog, The New Stack article) with web searches, since mekodata.ai's own website pages returned truncated HTML responses that did not expose readable content. The agent had to work around the site's inaccessibility by relying on 67% web search and prior knowledge to answer all four task components (what, who, pricing, differentiation). Pricing remained partially incomplete because the site's /pricing page was not machine-readable and no public tier costs were documented online.

• ›The mekodata.ai homepage and subpages (/, /pricing, /coding-agents, docs) all returned HTML that was truncated at 4400 characters, making them non-readable. The agent could not extract core content directly from the product's own domain.
• ›The agent successfully sourced what Meko does, who it's for, and competitive differentiation from external sources: Yugabyte's own blog post (step 21), The New Stack article (step 27), and database architecture documentation from web search results (step 31). These third-party sources contained substantive explanations of Datapacks, MCP integration, YugabyteDB architecture, and multi-agent memory positioning.
• ›Pricing information was the weakest part of the response. The agent confirmed free tier limits (1,000 conversational messages, 10,000 retrieval requests) but explicitly acknowledged it could not find Pro and Enterprise tier costs. The /pricing page on mekodata.ai exists but its content was not fetched successfully, and no public pricing documentation appeared in web search results.
• ›The site's discoverability was reasonable (web search returned official Yugabyte announcements, blog posts, and press coverage), but the primary product domain (mekodata.ai) was not agent-readable—suggesting either a front-end rendering issue, JavaScript-heavy content, or truncation in the fetch layer. The documentation site (docs.mekodata.ai) also returned truncated responses.
• ›The agent's final answer was citation-heavy and grounded in third-party coverage rather than primary sources. This is a workaround: the task asked the agent to 'read the site' and 'understand it well enough to explain it,' but the site itself did not serve machine-readable content, forcing reliance on secondary sources and external coverage.