The agent partially answered the task by assembling a coherent explanation of Crevio's positioning, target market, and pricing model, but had to work around the site's JavaScript-heavy frontend and missing pricing detail pages. Direct fetches of the homepage, pricing page, about page, and integrations page returned only HTML shells without readable content, forcing the agent to rely on web search results and prior knowledge (67% of sources) to fill in the gaps. The site is not agent-ready for this discovery task.

• ›Steps [1], [3], [5], [14] were cited as sources but returned only HTML boilerplate (DOCTYPE, meta tags, CSRF tokens) with content truncated — no actual readable product information, pricing tiers, or feature descriptions were extracted from direct fetches. The site is a client-side React/Next.js app that does not pre-render content for scrapers.
• ›The agent successfully constructed an answer by pivoting to web search (steps [7], [10], [11], [13], [16]), which returned third-party reviews (Findstack) and comparison articles hosted on crevio.co's own blog. These search snippets and referenced blog posts became the primary content-bearing sources — not the main site structure itself.
• ›The agent explicitly called out what it could NOT find: exact plan feature breakdowns, pricing page inaccessibility, clarity on the degree of autonomy required, and specific use case examples. The pricing table in the final response (Starter free, Creator ~$20-29/month, Business $50/month) was assembled from web search results, not directly fetched from crevio.co/pricing.
• ›The site's own blog and comparison articles (referenced in search results) proved more agent-readable than the main product pages, suggesting Crevio's content strategy favors organic search and SEO over direct product page accessibility. The agent had to treat crevio.co as a blog publisher to extract structured information about its own product.