The agent assembled a partial understanding of montoit.ca by fetching the homepage, about page, and search page, then supplemented with web search and a LinkedIn profile lookup. It successfully identified montoit as a condo aggregation platform for Montreal with data enrichment features, but could not find pricing or business model information—a critical gap that makes the explanation incomplete. The site's client-side rendering and missing documentation made content extraction difficult.

• ›Steps [1], [3], [5], [13], [14] returned Next.js-rendered HTML that the agent could not extract readable text from; the agent's final description of features (deduplication, deal scores, permit data, transit info, tax assessments) was inferred from its prior knowledge of similar platforms and web searches, not extracted from the site itself.
• ›Step [20] (LinkedIn) was explicitly cited as a source and confirmed the company has 16 followers and 6 employees, but provided no additional business model clarity.
• ›The agent correctly identified that `/pricing` returns 404 ([4]), and no pricing information exists anywhere on the traversed pages—this is a genuine site limitation, not an extraction failure. The agent called this out as a 'red flag' and explicitly stated 'I couldn't find any information suggesting how they make money or what the cost is to users.'
• ›The site offers no structured data (schema.org, API documentation, or machine-readable metadata) that would help an agent understand the service tier, revenue model, or feature set without JavaScript execution.
• ›The agent had to infer the core value proposition (aggregation, deduplication, analytical metrics) by reasoning from domain knowledge and search results, not from content it actually fetched and read from the site.