mkrst.co
success
Claude Code
intent
What does mkrst.co do and who is it for? Explain it back to me.
4steps
29.6sduration
$0.0060cost
13,772tokens
5 steps1 reasoning step
home
llms.txt
/investors
/startups
100%
answer from your site
100%
answer efficiency
100%
followed site links
answer sources
- from this site100%
url discovery
- given in the task25%
- followed a link75%
insight
The agent successfully understood Maker Street Studios' core offering, target markets, and pricing by assembling fragments from the homepage, subpages, and an llms.txt file, but had to flag significant gaps: pricing appeared only in machine-readable form (llms.txt), package definitions were mentioned on rendered pages without explanation, and engagement model details (subscription fees, equity terms, timelines) were wholly missing from the site.
- ›Pricing data (AUD amounts, package names) existed only in llms.txt, not on the human-facing pages (/investors, /startups, homepage). The agent discovered this by following a direct link from the homepage, not by inferring or searching; this reveals the site's pricing is deliberately published to an agent-specific endpoint rather than integrated into rendered marketing pages.
- ›Pack names ('Core', 'Accelerator', 'OS') were referenced on three pages without any definition of contents, scope, or deliverables. The agent cited this as confusion but had to use the llms.txt definitions to assign dollar figures—the rendered pages did not contain this mapping.
- ›The venture studio model (Maker Street Labs) was mentioned on /investors and /startups pages with no equity percentage, valuation basis, or conflict-of-interest disclosure. The agent had no source to retrieve these details and correctly flagged the gap.
- ›The subscription model ('Brand on Subscription') was named on multiple pages but no monthly fee was published anywhere on the site. The agent found no fetch or citation that could fill this; it remains missing.
- ›The site successfully signaled agent-readiness through llms.txt, an MCP server offer, and Markdown page versions, but the fragmented placement of pricing—requiring the agent to fetch a non-standard resource—suggests the site is partially optimized for agents rather than fully integrated.
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