bluewake.app
success
Claude Code
intent

What does bluewake.app do and who is it for? Explain it back to me.

17steps
70.4sduration
$1.0700cost
190,716tokens
26 steps9 reasoning steps7 searches
home
docs
docs
/features
/help
/guide
/faq
search
search
/api/conditions
search
llms.txt
search
search
/how-it-works
search
search
100%
on-site discovery
60%
reliability
60%
link following
path origin
  • previous resource60%
  • prior knowledge40%
insight

The agent successfully understood Blue Wake's core purpose, target audience, and differentiation by synthesizing content from the site's API endpoint and llms.txt file, but could not complete the pricing assessment due to absent or inaccessible pricing information. The site proved navigable for product discovery (API, documentation) but failed to surface pricing, business model, or mobile availability in any fetched or cited resource.

  • ›Step [14] (API endpoint /api/conditions) and Step [18] (llms.txt) were the only content-bearing fetches that powered the final answer. Both were machine-readable and explicitly cited. Step [14] returned live port data and score definitions; Step [18] returned the complete scoring algorithm, craft-type customization logic, data refresh cadence, and competitive positioning.
  • ›The agent never found a pricing page despite trying /pricing, /features, /help, and /guide — all returned 404s. The final response explicitly flags this gap and infers the service is free based on API/MCP availability, but this is an educated guess, not confirmed information from the site.
  • ›Step [23] (/how-it-works) returned a 200 but was JavaScript-rendered and unreadable to the agent, so no content was extracted from it. This suggests the site publishes detailed methodology on that page but does not expose it in a machine-readable form.
  • ›The site publishes an llms.txt file (step [18]), which is an agent-friendly artifact containing the full product description, scoring logic, craft-type variations, data sources, and API documentation — a significant affordance for AI-driven discovery.
  • ›Web searches (steps [11], [12], [15], [17], [20], [21], [24]) were routers or noise; none returned actionable information about Blue Wake's pricing, business model, or user base. The search results mostly surfaced competitor (KnowWake) information and generic boating app reviews.
  • ›The agent correctly identified that pricing is the only material gap and qualified the final answer appropriately, but could not fulfill the task fully because the site does not publish pricing information in any accessible form.

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