The agent successfully gathered a comprehensive explanation of InVideo.io's purpose, target audience, pricing, and competitive positioning, but relied heavily on third-party review and comparison sites rather than InVideo's own website. The homepage and pricing page fetches returned HTML but were not directly parsed into the final answer; instead, the agent synthesized information from external sources (Flowith blog, Cut the SaaS review, and AI Stack Picks comparison). The site proved difficult to navigate programmatically—the pricing page fetch succeeded but its content was not extracted, forcing the agent to bridge the gap with web search results and external reviews.

• ›Steps [6], [7], and [10] were the only content-bearing sources cited in the final response. Step [6] (Flowith pricing breakdown) provided the credit system details; step [7] (Cut the SaaS review) supplied feature and quality comparisons; step [10] (AI Stack Picks alternatives) delivered competitive positioning. None of these were InVideo's own pages.
• ›The agent's direct fetches of invideo.io/pricing and invideo.io/ (steps [1–2]) returned 200 status but their HTML was not parsed into usable content—the agent explicitly noted 'the pricing page content didn't load properly in my attempts to fetch it.' This forced reliance on external aggregators rather than primary sources.
• ›The /about page returned 404 (step [3]), indicating thin site navigation. The agent compensated by using web search (50% of fetch sourcing) to locate comparison and pricing reviews, which became the backbone of the answer. InVideo's own site did not surface sufficient structured metadata or clear feature/pricing matrices to be machine-readable for the agent.
• ›The agent was transparent about knowledge gaps: it flagged confusion around 'Agent Two' positioning, credit system rationale, and exact feature parity across tiers. These gaps reflect the site's marketing clarity problems, not the agent's diligence.