The agent successfully assembled a comprehensive explanation of Legba.app by fetching the homepage, pricing, about, docs, blog, and product pages directly, then supplemented gaps with web search to find the alternatives and OpenClaw pages. The site publishes its core positioning clearly on the homepage and pricing page, but pricing details are incomplete (vague tiers, custom enterprise quotes) and the distinction between product offerings (Cloud API vs. Sandbox vs. Extension) requires inference from scattered pages rather than explicit comparison. The agent had to work around truncated HTML responses that obscured actual page content, relying heavily on prior knowledge and search results to fill in the narrative.

• ›The agent fetched eight pages directly from legba.app (/, /pricing, /about, /docs, /blog, /product, /alternatives, /openclaw) but all returned truncated HTML (4,400+ chars truncated) with only metadata visible—the actual rendered content was not accessible, forcing reliance on search results and prior knowledge to extract concrete details about features, pricing tiers, and use cases.
• ›The pricing page ([3]) was fetched but its content was truncated, leading the agent to infer pricing from web search results rather than from the authoritative source. The agent learned about the $10/month Chrome Extension, $0–$5,000/month Cloud API, and custom enterprise tiers (Adversary, MSP) only after searching, not from direct page traversal.
• ›The site's alternatives/comparison content ([16]) and product page ([17]) exist and returned 200 status, but truncation meant the agent could not extract the actual competitive positioning from them—it had to rely on search snippets and prior knowledge of SquareX, Hyperbrowser, Browserbase, and Steel as alternatives.
• ›The agent discovered the /openclaw page ([22]) by inference from search results mentioning OpenClaw, not from site navigation. The direct structure of legba.app pages is sparse (most guessed routes like /features, /use-cases, /why-legba returned 404), forcing discovery through search.
• ›The agent explicitly cited eight pages in its sources section, all fetched directly from legba.app, validating that the site structure and URLs are stable—but the truncated responses mean the agent was unable to verify claims from actual page content and instead relied on search results and prior knowledge (54% of fetches sourced from prior knowledge).