The agent gathered a partial but coherent picture of showroom.so by fetching the homepage, pricing, and about pages, extracting core positioning (interactive polls, conversational forms, tests) and a three-tier pricing model (€5–€80/month). However, the site's reliance on Vue.js SPAs meant the HTML responses lacked detailed feature breakdowns, use-case examples, and explicit differentiation from competitors—forcing the agent to assemble an answer from meta descriptions and infer positioning from limited fragments, leaving significant gaps in what makes Showroom distinct.

• ›Step [0] (homepage) and steps [1–2] (pricing, about) were the only content-bearing fetches; they returned minimal, meta-description-level information. The actual site rendered via client-side JavaScript did not expose its full content to the agent's HTML parser.
• ›The agent correctly cited all three fetches in its Sources section, confirming they were genuinely used. Step [0]'s meta description ('Build and launch easy polls, conversational forms and clean educational tests') and step [2]'s description ('web-based flow creation tool') were the primary anchors for understanding what Showroom does.
• ›Web searches (steps [3–6]) were routing attempts that did not yield direct information about Showroom—they returned generic showroom definitions, competitor comparisons, and Zapier integration pages, none of which directly explained Showroom.so's differentiation. The agent acknowledged this in its final response ('I couldn't find articles directly comparing Showroom to alternatives').
• ›The site is poorly agent-ready: no structured data (schema.org), no plain-text feature lists in the HTML layer, no FAQ or help center links, and Vue.js hydration blocking full feature exposure. Pricing tiers exist but no feature matrix is visible in the fetched HTML.
• ›The agent's honest acknowledgment of what it could not find ('Detailed feature breakdown', 'Specific use cases', 'Target industries', 'Team/collaboration features') demonstrates awareness of its own epistemic limits—a sign it did not overstate confidence despite incomplete data.