Direct Answer: An AI Visibility Audit systematically inspects your website across four operational pillars: (1) Discover (Crawler Access): verification of robots.txt, HTTP status codes, and latency for 10+ AI crawlers; (2) Understand (Semantic Structure): validation of JSON-LD schema graphs (Organization, Service, FAQPage), entity disambiguation, and heading hierarchies; (3) Trust (Machine Readability & Evidence): direct-answer formatting, data citations, and /llms.txt availability; and (4) Recommend (Citation Share): empirical testing across ChatGPT, Perplexity, and Gemini for target commercial queries.
The 4 Operational Pillars of an AI Visibility Audit
Pillar 1: Discover (Crawler Access & Infrastructure)
- Verification of
robots.txtrules for AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Applebot-Extended). - Server-level WAF response codes, checking for silent 403 Forbidden or CAPTCHA barriers.
Pillar 2: Understand (Semantic Graphs & Entity Clarity)
- Validation of JSON-LD schema graph connectivity using consistent
@idanchors. - Presence of specialized schema subtypes (e.g.
Dentist,LegalService,LogisticsServicevs. genericLocalBusiness). - Verification of authoritative
sameAslinks connecting your domain to ACRA, SGDI, LinkedIn, and official industry registrations.
Pillar 3: Trust (Extractable Content Architecture)
- Evaluation of answer-first content density: testing whether core commercial queries are answered in the first two sentences.
- Validation of structured HTML tables and numbered process steps.
- Inspection of
/llms.txtfor machine-readable site navigation.
Pillar 4: Recommend (Empirical Citation Evaluation)
- Execution of standardized test prompts across ChatGPT, Perplexity, and Google Gemini.
- Measurement of brand citation presence, placement prominence, and competitive context.
Connected Knowledge Graph Topics
#Discovery Audit#Schema Check#Corroboration Signals#Recommendation Readiness