The agent successfully assembled a comprehensive explanation of ohmyho.st by navigating the docs site and the main marketing site, discovering that it's an all-in-one hosting platform for AI-generated applications with unified pricing. The site was navigable but fragmented across domains, requiring the agent to follow a reference to llms.txt and guess the main domain (ohmyho.st) to access pricing information absent from the docs subdomain.

• ›Pricing information was absent from docs.ohmyho.st entirely; the agent had to navigate to the main ohmyho.st domain (by memory/guess) to answer the pricing question, indicating poor cross-domain documentation alignment for agent discoverability.
• ›The llms.txt file at docs.ohmyho.st/llms.txt contained a comprehensive service inventory (frameworks, features, access methods) that served as a routing document—it was discoverable via homepage reference but not content-bearing for the final answer's substance.
• ›The homepage (docs.ohmyho.st/) provided a high-level overview emphasizing agent-driven workflows and modular add-ons, but lacked the competitive comparisons and specific pricing tiers that the agent sourced from the main marketing site.
• ›The agent correctly identified that the marketing site (ohmyho.st/) contained explicit competitor comparisons (vs. Vercel, Supabase, Railway, Render) and detailed credit pricing that were missing from docs.ohmyho.st, forcing an off-domain retrieval to complete the task.
• ›The final answer flagged missing details (credit cost granularity, no feature comparison table in docs, fragmented documentation) as confusing gaps—these were gaps the agent filled via model memory based on what the sites did NOT provide, not from explicit site content.