The agent successfully assembled a comprehensive explanation of SWR by combining the official documentation site (step [1]) with external sources from GitHub (step [4]) and web searches about comparisons and pricing (steps [2], [5], [6], [7]). The swr.vercel.app site itself was navigable but minimal—it provided basic structure and docs links, but the agent had to source 50% of its answer from web search and prior knowledge to fully answer the "what, who, price, and differences" questions.

• ›Step [1] (docs homepage) confirmed SWR exists and had a docs structure, but the homepage HTML was truncated in the response and did not explicitly state 'what is SWR' or pricing in machine-readable form.
• ›Step [2] (web search) was critical for discovery—it surfaced the GitHub repo and related articles that actually explained SWR's purpose (React Hooks for Data Fetching, Stale-While-Revalidate pattern).
• ›Step [4] (GitHub repo) provided authoritative content about the library's use case and features, but the agent relied heavily on prior knowledge and external comparisons (steps [5], [7]) to answer 'how it's different from alternatives' and 'who it's for'—information the official SWR site did not directly compare.
• ›Steps [5] and [7] (comparison and pricing searches) were necessary because the official swr.vercel.app site does not prominently state: (a) that SWR is free/open-source, (b) how it compares to TanStack Query, or (c) use-case recommendations. The agent noted this gap in its response ('the site doesn't explicitly highlight this upfront').
• ›The site's minimal structure and lack of explicit positioning/comparison content meant the agent had to reconstruct the answer from fragments, GitHub's README, and external expert comparisons rather than from a coherent narrative on the official domain.