The agent successfully gathered enough information to explain IntradayScreener's purpose, pricing, target audience, and competitive positioning, but had to rely almost entirely on web search results because the site itself is a JavaScript-heavy SPA that does not render content in fetched HTML. The agent assembled a coherent narrative from search result snippets and app store listings rather than from the site's own pages.

• ›Steps [1–6] fetched the site's main pages (/pricing, /about, /features, /faq, /docs) but returned only the HTML shell with no rendered content—all returned identical boilerplate with only Google Tag Manager scripts visible. The site is not agent-readable in its current form.
• ›The agent correctly pivoted to web search (steps [8–14]) and found information from search result metadata, Google Play/App Store listings, and third-party comparison sites (Similarweb, StockGro, Cup of Glory). These searches were content-bearing and explicitly cited in the final response.
• ›Key facts were scattered: pricing came from search result titles; feature differentiation came from app store descriptions and comparison articles; competitive positioning came from traffic data and category rankings. The agent had to synthesize these fragments into a coherent answer rather than reading from one authoritative source.
• ›The site's own URLs appear in search results (steps [8–9] return intradayscreener.com/pricing as a link), but fetching those URLs yields no usable content. This creates a disconnect between what search engines index about the site and what the site actually serves to programmatic clients.
• ›Prior knowledge was responsible for 71% of fetches (steps [1–6], [10] were all guesses at common URL patterns), but those guesses yielded no actionable content. Web search (0% sourcing officially recorded, but steps [8–14] were clearly the productive path) provided the actual answer.