mapaterraplanagem.com.br
success
Claude Code
intent

What does mapaterraplanagem.com.br do and who is it for? Explain it back to me.

8steps
47.4sduration
$0.4238cost
69,955tokens
14 steps6 reasoning steps3 searches
home
home
search
/servicos
/sobre
/reservatoriosebarragens
search
search
100%
on-site discovery
80%
reliability
80%
link following
path origin
  • previous resource80%
  • prior knowledge20%
insight

The agent successfully assembled a comprehensive overview of Mapa Terraplanagem by retrieving and synthesizing content from the homepage and two service pages, identifying what they do, who they serve, and how they differentiate. However, the site's lack of published pricing information forced the agent to work around a significant gap—it could only document that pricing is custom-quoted rather than provide actual rates. The site was moderately navigable for discovery but deliberately opaque on commercial terms.

  • ›Steps [1] and [3] (homepage fetches) provided meta descriptions and structural understanding of the three core services (reservoirs/dams, geomembranes, topography) and the 15-year track record claim, but both returned truncated HTML (4400+ chars cut off) limiting access to full page content.
  • ›Steps [7] and [8] (About and Reservoirs & Barragens service pages) returned service-specific details and compliance information (ART, ABNT standards, IAGI references), confirming positioning around certification and technical rigor rather than price leadership.
  • ›The site does not publish pricing or case studies publicly—the agent correctly identified this absence and noted it as a deliberate gap. Web search steps [5], [10], [12] found no pricing on the domain itself, only generic industry benchmarks from competitors, indicating Mapa Terraplanagem operates on a 'call for quote' model.
  • ›Navigation was fragmented: step [6] encountered a 404 at /servicos (attempted based on homepage link inference), forcing the agent to pivot. The agent had to guess or infer the correct service URLs (/sobre, /reservatoriosebarragens) rather than discover them from a sitemap or menu. This suggests either poor site structure visibility or JavaScript-rendered navigation that the agent could not fully extract.
  • ›The site's JavaScript-heavy frontend (noted in final response) impeded full content extraction, requiring the agent to rely on metadata, truncated fetches, and prior knowledge (20% of sourcing) to fill gaps. The agent did not attempt to access a sitemap, robots.txt, or structured schema (JSON-LD) to find all pages systematically.

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