The agent successfully assembled a comprehensive overview of Motion's value proposition, pricing, and differentiation, but had to work around an inaccessible primary domain (motion.com blocked by Cloudflare) and rely heavily on web search to discover the product site. The core product information came from usemotion.com pages directly fetched, but key details like the credit system mechanics and AI Employees specifics remained unclear because the site's marketing materials did not explain them in sufficient depth.

• ›Step [4] (usemotion.com/pricing) and step [9] (usemotion.com/features/ai-calendar) were the only direct fetches of official Motion content that yielded substantive product information. Step [6] (usemotion.com homepage) provided high-level positioning but the response was truncated, limiting how much detail was actually extracted.
• ›The agent discovered Motion's actual domain (usemotion.com) entirely through web search results, not by following navigation from motion.com. The primary domain was unreachable (Cloudflare challenge); 67% of the agent's fetch sources came from web search, indicating the site was not self-discoverable and required external search routing.
• ›The site exposed pricing tiers and feature names clearly (Pro AI, Business AI, credit amounts, feature lists), but omitted crucial details: how credits are consumed per-feature, exact team vs. individual pricing differences, and concrete examples of what 'AI Employees' actually do. The agent had to flag these as missing information rather than infer them.
• ›The agent cited three official Motion URLs as sources but relied on external comparison articles (reclaim.ai/blog/motion-alternatives, cybernews.com, etc.) to extract differentiation claims. Motion's own site does not appear to have a dedicated 'vs. competitors' or 'why Motion' page that answers the 'how it's different' question directly.
• ›The site's HTML responses were heavily truncated (4400+ chars) in the trajectory, suggesting large payloads that may not have been fully parsed. This is a data richness vs. agent-readiness tradeoff — the site may publish more than the agent could extract.