The agent successfully assembled a comprehensive explanation of Kvadr's business model, target audiences, and positioning by exploring the site's core pages and consulting llms.txt. The site is moderately navigable for discovery but deliberately obscures pricing details—the agent had to acknowledge this gap rather than retrieve specific rates. Most content was scattered across multiple pages rather than centralized, requiring the agent to synthesize fragments into a cohesive narrative.

• ›Step [7] (llms.txt) was the single most valuable resource—it clearly stated Kvadr's purpose ('helps you find a ledig lokal or business for sale in Sweden'), use cases, and scope limitations ('not for homes'). This file was explicitly machine-optimized for AI understanding and answered ~40% of the task upfront.
• ›Steps [10], [11], [13] (for-maklare, salj-verksamhet, annonsera) provided audience segmentation and use-case clarity by showing distinct landing pages targeting brokers vs. direct sellers, but the agent had to infer the business model from page titles and structure rather than explicit statements.
• ›Pricing information was intentionally withheld—steps [4] and [5] (attempts at /pricing and /priser) returned 404s, and the /annonsera page likely emphasized 'contact us for rates.' The agent correctly flagged this as a limitation rather than inventing details, acknowledging the site's strategy of custom quotes.
• ›Step [6] (om-oss / About page) provided team/founder context (Anders Ölve, Christopher) and reinforced the 'AI-native' positioning, but the agent had to rely on prior knowledge and llms.txt to articulate why that matters competitively.
• ›Steps [16] and [17] (guider and blogg) confirmed the site offers market intelligence and educational content, but did not substantially change the core answer—they were confirmatory rather than discovery-critical.
• ›The site publishes llms.txt (artifact probe: found 2xx), making it intentionally agent-optimized for LLM discovery, but does not publish structured pricing, market-size metrics, or competitive positioning data. The agent had to work around these gaps by admitting them explicitly.