The agent assembled a comprehensive explanation of Partial.ly's business model, target users, pricing, and differentiation from competitors by combining direct site content (homepage, pricing, platform, solutions pages) with external third-party reviews and blog posts. The site itself was only moderately navigable—core pages loaded but were React-rendered with truncated content, forcing the agent to rely heavily on web search results and external sources (64% of fetches sourced from web search) to fill gaps about features, use cases, and competitive positioning.

• ›Steps [1], [3], [4], [7] returned meta descriptions and truncated HTML from React-rendered pages—the site's core value proposition (merchant-financed payment plans, no credit checks, 100% approval, transaction fee pricing) was present in these snippets but full feature details were inaccessible via static fetch.
• ›The agent could not load detailed feature content directly from partial.ly and instead found concrete information in external sources: step [23] (blog.partial.ly article on customer experience) and step [25] (SoftwareSuggest review) provided use cases and feature clarity that the marketing pages did not expose in fetchable form.
• ›The site's structure created discovery friction: attempted direct navigations to /help, /how-it-works, and /invoicing all returned 404s or fallbacks to the homepage (steps [6], [15], [16]), forcing the agent to rely on web search to map the product surface.
• ›Pricing information was initially vague in fetches—the agent inferred the $10/month + 2% transaction fee model from meta descriptions, but one external source mentioned '5% + $30' fees, creating ambiguity the agent flagged as unresolved.
• ›The agent correctly identified what it could NOT find from the site alone: default/non-payment handling, granular fee structure clarity, customer credit risk evaluation guidance, detailed feature lists, and regulatory considerations—these gaps were acknowledged in the final response rather than guessed.