The agent successfully assembled a comprehensive explanation of Depot's products, pricing, and positioning by combining structured documentation fetches with web search. The site published most content in machine-readable markdown form (via `/docs/*.md` endpoints and `llms.txt`), but the pricing page itself was React-rendered and inaccessible to direct fetch—forcing the agent to rely on web search results and prior knowledge to extract specific pricing numbers. The core narrative was well-sourced from documentation; pricing details and competitive claims required bridging.

• ›Steps [6], [9], [10], [12], [13] returned markdown documentation that directly answered 'what they do' and 'who it's for': Container Builds (40x faster), Depot CI (GitHub Actions replacement), GitHub Actions Runners (3x faster), Cache, Registry, and Remote Agents for AI coding.
• ›Step [3] (pricing page fetch) returned a 200 but served a React app skeleton with no pricing text content—the agent could not extract pricing details from the HTML response and had to rely on web search results (steps [15], [16]) and prior knowledge to populate the pricing section with specific numbers ($20/month, $0.04/min, second-based billing).
• ›The site publishes `llms.txt` (step [7]) with a structured index of documentation URLs, and `/docs/*.md` endpoints serve raw markdown—both machine-readable patterns. However, pricing details were not included in the markdown bundle, and the main pricing page was client-rendered, reducing agent navigability for that critical section.
• ›The agent correctly identified and called out gaps: React-rendered pricing page, unclear free tier limits, ambiguous product bundling discounts, and sparse enterprise documentation—demonstrating awareness of what it could not directly retrieve.
• ›Steps [15] and [16] (web search) were routers pointing to external comparison sites and the same pricing URL, not content-bearing; the agent's final response cited sources including these searches, but the actual pricing data came from prior knowledge or snippets, not from traversing the search results.