The agent successfully gathered comprehensive information about Requesty by fetching the site's markdown documentation files (index.md, llms.txt, pricing.md), which contained the core product definition, pricing model, and feature list. The site publishes its core content in machine-readable markdown form at predictable paths, making it highly navigable; however, the agent had to assemble a competitive comparison from external blog sources rather than from Requesty's own site, and encountered minor inconsistencies (400+ vs 600+ models) that suggest documentation drift.

• ›Step [4] (index.md) and step [8] (pricing.md) returned well-structured, content-rich markdown that directly answered 'what they do' and 'how it's priced' — the site publishes canonical product explanation and pricing in fetchable text form rather than hiding it behind interactive UI.
• ›Step [6] (llms.txt) provided an alternative product summary that described competitors by name (Kong, Cloudflare, LiteLLM, Portkey, OpenRouter, Helicone), which helped seed the competitive analysis, but the actual comparison details came from external blog posts, not from Requesty's own site.
• ›The site's use of predictable markdown routes (/index.md, /pricing.md, /llms.txt) and a docs subdomain (docs.requesty.ai) with Mintlify hosting shows strong agent-readiness for discovery and identity questions; however, detailed technical differentiation (how routing actually works, performance benchmarks) was not present in the fetched pages and would require either deeper docs navigation or external sources.
• ›Minor friction point: homepage claims '600+ models' while llms.txt claims '400+ models' — suggests content is maintained separately and may drift; agent noted this discrepancy but had to proceed with incomplete clarity.