How the audit works.
Four categories. 47 checks. 100 points. Every weight maps to published research on how AI platforms decide which sources to cite.
The 4 categories
Whether AI crawlers can discover, reach, and read your site before any other optimization matters.
- AI crawler permissions in robots.txt
- Rendered HTML vs JavaScript shell, CDN access rules
- HTTPS, sitemap, canonical, and indexing signals
Content shaped for chunk-level AI retrieval — direct answers, clear headings, fact density, recency.
- Question-format headings and a direct answer near the top
- Named sources and verifiable claims in body text
- dateModified signals and content that reads as current
Machine-readable markup and clean page structure that communicate your identity and content accurately.
- JSON-LD schema in the head, correctly typed
- Schema values consistent with visible page content
- Heading hierarchy, Open Graph tags, image alt text
Earned third-party authority, a clear entity identity, and whether you appear in live AI responses right now.
- Brand mentions, referring domains, and earned media
- Entity disambiguation: disambiguatingDescription, profiles, Wikidata
- Live probes across ChatGPT, Perplexity, Google AI Overviews, Claude
Scoring & methodology detail
How the score is calculated
Each category contributes a sub-score based on specific checks against the site. The sub-scores combine to produce the overall 0–100 result, which maps to a letter grade:
| Grade | Score | |---|---| | A | 85–100 | | B | 75–84 | | C | 60–74 | | D | 40–59 | | F | 0–39 |
Every check in the audit maps to evidence from the academic and industry research on AI citation mechanics. No check is included without a published-research justification. The full check-level breakdown is included in the paid audit report.
What the score is — and what it is not
The score is diagnostic. It tells you where you stand across the four dimensions that AI platforms rely on when deciding which sources to cite. A higher score means fewer barriers to citation and more of the positive signals AI engines look for.
The score is not a guarantee of citation. AI search platforms make ranking decisions based on hundreds of signals, many of which shift week to week. An audit captures a snapshot of your current technical and content posture — it does not predict specific placement outcomes.
The audit uses an evidence-informed weighted rubric. The category weights reflect the relative importance of each dimension based on available research, not a proprietary black box. Every weight is explained and the rationale is public.
How the live probes work
The Trustworthy Authority category includes live queries to four AI platforms — ChatGPT, Perplexity, Google AI Overviews, and Claude — using prompts generated from your brand name, business type, and location or ICP. Each prompt is run three times to capture within-session variation. The results feed directly into your score and appear as a per-platform grid in the audit report.
This is the only part of the audit that produces direct empirical evidence of how AI platforms respond to queries about your business right now.
What the score is not
Results are directional, not gospel.
After implementing improvements, AI citations typically appear within a few weeks on Perplexity, a month or more on ChatGPT, and several months on Google AI Overviews. These are directional ranges, not timetables. Every platform is different and timelines vary by category and competitive density.
Even well-optimized pages see meaningful variation in citation frequency across weeks. No audit can guarantee stable citation rates, because the platforms themselves change continuously — in training data, in retrieval logic, and in response formatting. Re-audit every 30 days for trend signal rather than treating a single run as definitive.
In densely competitive B2B verticals, reaching consistent AI citation may require a longer horizon. The audit scores your position in absolute terms; relative competitive density is an additional factor.
The audit tells you what to fix and why it matters. It does not promise a specific lift in citation rate. AI visibility improvements are directional and evidence-informed — not deterministic.
The live probes included in the audit sample AI responses at a point in time. Longitudinal trends require repeated runs. Treat the first audit as a baseline and compare against subsequent audits to measure directional progress.