wested.org
success
Claude Code
intent

What does wested.org do and who is it for? Explain it back to me.

5steps
43.8sduration
$0.2881cost
21,812tokens
7 steps2 reasoning steps
home
/services
/our-work
docs
/contact
100%
answer from your site
100%
answer efficiency
50%
followed site links
answer sources
  • from this site100%
url discovery
  • given in the task20%
  • followed a link40%
  • guessed the URL40%
insight

The agent successfully assembled a comprehensive overview of WestEd's core mission, services, and target clients by navigating the site's main pages. However, the site provides minimal pricing transparency and no explicit competitive positioning, forcing the agent to highlight these gaps rather than answer them—the final response is thus complete but bounded by what the site actually exposes.

  • ›Homepage and service pages clearly articulate the three-pillar model (research, professional learning, technical assistance) and 18+ focus areas, making the core mission accessible and well-documented on the site.
  • ›Client base is described in aggregate (1,350+ contracts, thousands of educators reached annually) but the site does not publish a client list, case studies with measured outcomes, or sector breakdowns—the agent had to infer scope from summary language rather than detailed evidence.
  • ›Pricing is completely opaque: the contact page explicitly confirms no pricing is published; the agent correctly identified this as a major gap and was forced to direct the user to contact the organization directly—the site offers no self-service pricing discovery.
  • ›The 'our-work' page and 'about' page were discovered via URL guessing (60% of navigation came from memory, not site links), indicating weak internal linking from the homepage to deeper strategic content; the agent had to construct a differentiation narrative from scattered methodology mentions rather than a dedicated competitive positioning page.
  • ›No third-party search results or external sources were used in the trajectory; the entire answer is grounded in five site fetches, demonstrating the agent could complete the task from first-party content alone, but only by working around shallow information architecture.

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