AXOgrade

Direct-to-consumer merchants need to know whether machine clients can parse products, current price, availability, policies and supported transaction paths. AXOgrade crawls authorized public surfaces, validates declared feeds and interfaces, records evidence, and presents dimension-level findings with confidence and remediation. The supplied research confirms adjacent AI-visibility dashboards and a content product, but no direct six-axis commerce-agent audit. It also confirms widespread automatic deployment of llms.txt while empirical logs show no major AI crawler reading it; presence must therefore be reported as a convention, not scored as proven discoverability. Zero referenced APIs are verified, so transaction tests require merchant-declared specifications and safe non-purchasing modes until independently validated. A readiness score is a transparent summary of observable checks, not a prediction of recommendation, rank, traffic, conversion or revenue. Merchant trust is limited to machine-readable policy and identity evidence and never becomes a legitimacy rating. Crawl observation, validation, remediation candidate, merchant change, re-test, agent behavior, referral, checkout, order and commercial outcome remain separate. Success is fewer observable machine-readability defects—not guaranteed agent access or a universal standard.

A DTC ecommerce, merchandising, growth or technical-SEO leader responsible for catalog quality and emerging shopping-agent channels.