The agent assembled a reasonably complete overview of Get New Resume's core offering, pricing tiers, and competitive positioning, but encountered significant friction due to the site's JavaScript-heavy rendering and incomplete feature documentation. Key information about what the service does and who it's for was inferred from metadata and web search results rather than extracted directly from the site's content; the pricing page existed but didn't load legibly, and feature-tier breakdowns remained unclear despite multiple page fetches.

• ›The homepage, pricing page, about page, and FAQ all returned valid 200 responses but were Next.js/React bundles that truncated in the response, preventing the agent from accessing written content—the agent had to rely on page titles and metadata in search results rather than the actual page bodies.
• ›The agent successfully inferred the core value proposition (AI resume tailoring, truth-based philosophy, ATS matching) from search result snippets and metadata, but this required web search fallback; the site itself did not surface this information in a machine-readable or easily-parseable form.
• ›Pricing tier feature breakdown (what each tier unlocks) was never clarified despite fetching /pricing—the agent noted tiers exist ($9.99, $29.99) but could not determine free-tier limits, application count caps, or feature lockouts, indicating the pricing page either did not load or contained only visual/interactive pricing comparison that was not captured.
• ›The /how-it-works URL returned 404, suggesting either a missing page or a URL mismatch; the agent had to guess the correct navigation structure.
• ›Competitor positioning (vs. Rezi, Kickresume, etc.) was inferred from web search comparisons, not from on-site content, suggesting Get New Resume does not publish direct competitive analysis on their own domain.