The agent gathered a partial understanding of Posteady by combining a direct site fetch (which returned compiled Next.js markup lacking readable content), one search result snippet that confirmed Posteady as 'Free Social Media Cross-Posting & Analytics Platform', and a third-party review article. The site's dynamic rendering and lack of accessible pricing/feature details on the homepage meant the agent relied heavily on search results and prior knowledge rather than on-site content, and could not retrieve detailed pricing tiers, feature comparisons, or differentiation specifics.

• ›Step [1] (homepage fetch) returned Next.js-compiled HTML with no readable content or structured data—the site's full information is client-side rendered and inaccessible to static scraping. This forced the agent to pivot to search.
• ›Step [6] (first search for 'posteady.com what is it social media') returned a snippet confirming the core value proposition ('Free Social Media Cross-Posting & Analytics Platform') but no pricing or feature details. This single search result snippet became the primary source of truth for the agent's main claim.
• ›Step [11] (posteverywhere.ai blog on scheduling tools) was fetched to find comparative reviews but also returned compiled Next.js markup with no readable content, limiting comparative insight.
• ›The agent could not access the pricing page (step [3]) or about page (step [4]) in readable form—both returned the same compiled Next.js boilerplate. Subsequent targeted searches (steps [7], [10], [13]) for pricing tiers and feature comparisons returned only links to Posteady's own homepage, not third-party reviews or comparisons.
• ›The agent explicitly flagged gaps: detailed pricing tiers, feature differences between free/paid, monetization model, founder/team info, and head-to-head competitor comparisons. These were never retrieved because the site does not publish them in a way discoverable via search or static fetch.
• ›The final answer relied on ~50% prior knowledge (inferred positioning against Buffer/Hootsuite), ~25% search snippet text, and ~25% general web search results—very little came from Posteady's own published content.