What is wrong? Where? What does it affect?
The free scan shows the finding, affected URL and evidence.
- Technical findings and affected URLs
- Severity and confidence
- Impact × Effort priority view
- Implementation code and instructions: NONE
The free scan shows the finding, affected URL and evidence.
Turns measured findings into an execution order your technical team can implement.
The free scan exposes the problem; the paid layer makes measured findings actionable and testable.
Evidence and URL.
Which technical or discovery path is affected.
The next step your developer can execute.
Acceptance, regression and rollback.
Send the free diagnostic first; the buying decision only happens when measured issues require implementation.
These are not illustrative labels; they are the canonical server-generated delivery manifest.
00_READ_ME.md01_EXECUTIVE_SUMMARY.md02_IMPLEMENTATION_BLUEPRINT.md03_FINDINGS.json04_ACCEPTANCE_TESTS.md05_ROLLBACK_PLAN.md06_AI_READINESS.json07_IMPLEMENTATION_CHECKLIST.txtHTML&HTML audits public website surfaces, shows evidence for each finding, and prioritizes a fix path your technical team can execute.
Evidence boundary: External-model recommendation, ranking, citation, traffic or revenue is not guaranteed. Unavailable evidence stays NOT_MEASURED; code context stays REQUIRES_CONTEXT.
Paid delivery boundary: up to 30 evidence-bound page-level Markdown machine surfaces and a versioned ZIP delivery package.
Diagnosis is free. The paid product converts measured blockers to AI search visibility and source eligibility into a testable implementation prescription.
robots.txt, sitemaps, canonicals, indexability and AI crawler access form the discovery foundation.
GEO, AEO, LLMO, entity graphs, schema and answer extractability reduce machine ambiguity.
RAG/retrieval, original information, E-E-A-T, freshness and evidence support source eligibility.
AAO, accessible journeys, intact links, measurable referrals and clear CTAs connect AI discovery to commercial action.
Recommendations, rankings, citations, traffic, customers and revenue are not guaranteed. HTML&HTML measures website-side technical and content blockers; it does not claim control over external AI systems.
Google publishes official guidance for generative AI Search, recognizes GEO/AEO as market terms but treats this work as SEO for Google Search, says there are no special extra AI Overview/AI Mode requirements, and says Google Search does not use llms.txt for this visibility.
Open source ↗OpenAI says any public website can appear in ChatGPT Search and OAI-SearchBot access helps content be discovered, surfaced, clearly cited and linked.
Open source ↗Google announced dedicated generative AI Search visibility reporting in Search Console and worldwide rollout in 2026.
Open source ↗