The agent successfully assembled a comprehensive explanation of Firecrawl by combining fetches from the official site (homepage, pricing, docs) with external third-party sources (review sites, competitor comparisons, pricing analyses). The official Firecrawl site itself was navigable but sparse on details—pricing page and docs existed but required supplementation from external sources to answer 'how it's different' and clarify pricing gotchas. The agent had to rely heavily on external reviews and comparison articles (50% of fetches sourced from web search) to provide a complete answer, indicating the official site under-indexes competitive positioning and pricing edge cases.

• ›The official Firecrawl homepage and pricing page (steps [1], [3]) returned valid pages but were light on specifics—no pricing table, no clear feature differentiation. The agent reconstructed pricing details primarily from third-party sources (eesel.ai, affinco.com, dev.to pricing teardowns in steps [13], [14]).
• ›Competitor comparison was entirely sourced from external articles (thunderbit.com, context.dev, brightdata.com, medium.com in steps [8], [9], [14]). The official site does not publish structured 'vs. alternatives' comparisons; the agent had to hunt for third-party evaluations.
• ›The docs site (step [4]) was fetched but appears to have been used mainly for API endpoints overview; deep feature explanations came from external sources and prior knowledge (the trajectory shows 17% prior knowledge usage, likely domain familiarity with web scraping APIs).
• ›Three content gaps remained unfilled despite the search-heavy approach: success rates, concurrent request limits, and detailed 'Agent' mode pricing/mechanics—suggesting even external sources don't document these thoroughly.
• ›The agent's final answer cites 13 sources, of which ~8 are external review/comparison articles and only 3–4 are official Firecrawl URLs, revealing reliance on secondary sources to answer the core discovery-evaluation task.