Live Machine-Readability Diagnostic
See exactly what AI buying agents read.
The LeverageIQ Readiness Scanner executes six parallel server-side HTTP probes against any public domain to score nine dimensions of agentic commerce readiness out of 100 points.
Test any domain against all nine readiness ribs.
Run a live server-side HTTP inspection across SSR HTML latency, zero-JS readability, JSON-LD entity graphs, AI crawler permissions, llms.txt, UCP, ACP, and AP2 cryptographic trust. Each passing dimension illuminates its corresponding scanning rib on the 3D Astrolabe.
Nine armillary scanning ribs correspond 1-to-1 with SSR latency, semantic readability, JSON-LD @graph, crawler rules, llms.txt, UCP, ACP, AP2, and canonical provenance.
Nine-Rib Scoring Methodology (100 Points)
Measures raw server-side HTML response latency. Autonomous retrieval agents enforce strict timeouts and penalize slow client-hydrated shells.
Counts extractable body copy without executing JavaScript bundles so LLM crawlers read complete offers and pricing.
Validates linked Organization, Person, WebPage, Service, SpeakableSpecification, and FAQPage nodes.
Checks robots.txt rules for GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, and PerplexityBot.
Verifies presence of a clean markdown /llms.txt index summarizing capabilities and canonical routes.
Probes /.well-known/ucp for machine-readable merchant identity, catalog capabilities, and REST/MCP bindings.
Probes /.well-known/acp/config.json for deterministic quote negotiation and settlement rail rules.
Probes /.well-known/ap2/mandates.json for public ECDSA P-256 JWK keys and JWS verification endpoints.
Confirms canonical link tags, single semantic H1 hierarchy, and high-signal meta descriptions.