Signal 09 of 09 · Nebula Diagnostic Spec v1.0.0
AI Readiness
Can answer engines identify, verify, and cite the page accurately?
Decision rule
Machine-facing surfaces must let AI systems resolve who you are, what you offer, and what claims are supportable: structured data matching visible content, explicit factual statements, stable entity references, and crawler policy that permits answer engines you want citing you.
What the engine inspects
- ·JSON-LD presence and accuracy
- ·entity consistency
- ·claim specificity
- ·crawler access rules for AI agents
How to check it yourself
- Validate structured data (Rich Results Test or a JSON-LD parser) against what the visible page actually claims.
- Check the company and product are described consistently across pages, schema, and profiles.
- Read robots.txt and confirm the answer engines you want citing you are not blocked.
The engine automates this inspection and attaches measured evidence to every failing condition. A manual pass is not a substitute for the recorded evidence trail, but it should agree with it.
Pass / fail examples
Pass
Product schema matches visible pricing; company identity is stated once, consistently, with same-as links. Clear.
Fail
Schema asserts guarantees the visible page never makes, and robots.txt blocks every AI crawler indiscriminately. Flagged.