The agent successfully understood Kanz by retrieving four markdown documentation pages that directly contained the core information: what the product does, pricing structure, competitive positioning, and FAQ answers. The site was highly navigable for machine reading—it published structured markdown versions of all key pages, which the agent discovered via prior knowledge and followed links. However, the agent had to rely on prior knowledge to find the markdown routes; the HTML pages alone (steps [1–3]) would not have yielded usable content.

• ›Step [5] (index.md) contained the complete value proposition and feature set in structured markdown; step [6] (pricing/index.md) provided exact pricing tiers and credit costs; step [9] (alternatives/index.md) exposed the competitive comparison table the user asked for; step [10] (faq/index.md) answered questions about implementation and constraints.
• ›The site publishes markdown versions of all major pages alongside HTML, making it machine-readable and citation-friendly. The agent discovered this through prior knowledge (38% of sources) rather than following HTML navigation—the HTML pages returned were JavaScript-heavy and truncated, not useful for extraction.
• ›The site is well-structured for agent navigation once the markdown pattern is known: metadata headers (language, last updated, source URL), clear headings, and tables. However, without prior knowledge of the /index.md pattern, an agent would have struggled with the HTML-only homepage and gotten stuck at step [3] (404 on /features). The site does not advertise or link to its markdown documentation in the HTML responses.