Per our own AI-Overview audit of 1,026 buyer queries (June 2026), 879 returned an AI Overview and 233 of those cited FORKOFF.
FORKOFF · Tools
Paste a URL. We compose AEO (page HTML signals) + GEO (domain agent-readiness) + Lighthouse (technical SEO) into one unified score, plus a 6-dimension fix-list across schema coverage, AEO snippet ownership, internal linking, answer-engine readiness, and freshness. Want one dimension instead of the composite? Use AEO Checker for page signals, GEO Audit for domain substrate, or AI Search Visibility Checker for per-LLM citation share.
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The audit scores Schema.org coverage, AEO snippet ownership, LLM citation surface, internal linking, answer-engine readiness, and freshness + author signals, weighted to reflect what actually moves citations on the FORKOFF managed-engagement ledger. Since Schema.org coverage is the lever most sites score worst on, our guide to schema markup for AEO is the fastest place to start fixing it.
The weighted average is dragged down by any dimension under 40. Pulling the bottom dimensions into the 55+ band is the highest-leverage move; flagship dimensions above 75 hold the ceiling.
47
Median composite · un-optimized 2026 pages
200+
Pages in the calibration corpus
0-100 per dimension. Anything below 50 is a fix priority. Anything above 75 is defended. The audit weight column anchors the composite calculation.
Lit cell = page cited by that LLM on that query. Even one citation in the grid lifts the citation-surface dimension materially.
Article + Org + BreadcrumbList present at baseline. FAQPage + HowTo + Author are the highest-leverage missing types. Each fills 4-8 composite points.
Surface dimensions move at T+30. LLM citation surface catches up T+60 to T+90 as engines re-crawl + re-weight. Tier-A pages stay there with quarterly re-audits.
Inputs
Page URL. The specific URL to audit. Audit scope is the single page + first-degree internal links, not a full domain crawl.
Target query set. 5-15 commercial queries the page should rank + be cited on. The query set anchors the AEO snippet ownership + LLM citation surface dimensions.
Optional · competitor URLs. Up to three competitor pages on the same query set, for relative scoring.
Outputs
Per-dimension scores (0-100). Schema.org coverage · AEO snippet ownership · LLM citation surface · internal linking · answer-engine readiness · freshness. Six numbers + the rule applied.
Composite score + tier. 0-100 weighted average. Tier-A (75+) cite-ready · Tier-B (55-74) needs targeted lift · Tier-C (40-54) restructure · Tier-D (<40) rebuild.
Prioritized fix-list. 6-14 specific changes, ordered by score-lift / effort. Each entry names the dimension, the change, and the projected score lift.
AI SEO Audit composes three pillars into one unified score: AEO Checker (page HTML signal, 40% weight), GEO Audit (domain agent-readiness substrate, 40% weight), and a mobile Lighthouse audit (technical quality, 20% weight). Run any URL through one form and get back the composite plus per-pillar breakdown plus a cross-pillar remediation queue ordered by composite-gain-per-effort. Use it as the single number when you want the full AI SEO picture instead of three separate audits.
Each card is a real audit cell from the FORKOFF managed-engagement ledger. Run the live tool above on your own URL to score it.
Scenario 01
Tier-CAI agency service page · pre-audit
Established service-page ranking #6 on Google for primary commercial query. No FAQPage schema, no Author schema, 0 LLM citations.
Composite
47
Recommendation
Add FAQPage + Author schema (8 + 4 points). Publish 12-question FAQ block (+8). Earn 3 inbound citations from cited-by-LLM domains (+10). Target Tier-B in 30 days.
Scenario 02
Tier-BWeb3 protocol comparison page
Comparison page ranking top-3 on commercial query. Solid schema, weak answer-engine structure. Cited by Perplexity but not by ChatGPT.
Composite
68
Recommendation
Strengthen answer-engine surface (+9 from FAQ + HowTo). Add primary-source citations (+5). Push for ChatGPT cite by earning 2 inbound links from chat-cited domains (Stack, Reddit, Wikipedia adjacency).
Scenario 03
Tier-DPre-launch SaaS landing page
New page, no rankings yet, full schema implementation, weak internal linking + freshness signals. Zero LLM exposure.
Composite
39
Recommendation
Tier-D = rebuild before re-audit. Add a topic cluster around the page (5+ spokes), publish weekly, earn 3+ inbound links. Re-audit at T+45.
Scenario 04
Tier-AFORKOFF service-page baseline
/services/ai-seo-services · full schema · FAQ + HowTo · 3 LLM citations on commercial query · Author + last-updated signals.
Composite
82
Recommendation
Defend. Re-audit quarterly. Push citations dimension above 90 by earning a Wikipedia adjacency or a top-3 Perplexity source slot for the head query.
Ahrefs / SEMrush / Screaming Frog measure rank + crawl + tags. AI SEO Audit measures whether ChatGPT cites the page on its target queries: the surface those tools don't see.
← scroll horizontally to see more →
| Feature | FORKOFF AI SEO Audit6-dimension AI-native audit + LLM citation measurement | Ahrefs / SEMrushRank + link profile + Core Web Vitals | Screaming FrogOn-page crawl + tag audit | Surfer / ClearscopeContent optimization scoring |
|---|---|---|---|---|
| Measures LLM citation surface across 5 engines | ||||
| Audits Schema.org @graph completeness for AI search | partial | |||
| Scores AEO snippet ownership on commercial queries | partial | |||
| Returns prioritized fix-list ranked by score-lift / effort | partial | |||
| Free, no signup, no domain claim | ||||
| Best for ranking + backlink monitoring on existing pages | partial | |||
| Best for surface-level on-page tag audit | partial |
If your decision lands in the left column, the audit is the right surface. If it lands in the right, use a different tool.
Built for this
Not the right fit
An AI SEO audit scores a page on its LLM-citation surface (whether ChatGPT, Perplexity, Claude, Gemini, and Grok cite the page on its target queries) across six AI-native dimensions (Schema.org coverage, AEO snippet ownership, LLM citation surface, internal linking, answer-engine readiness, freshness + author). A regular SEO audit (Ahrefs, SEMrush, Screaming Frog) scores rank position + link profile + crawl health. The two are complementary; a Tier-A AI SEO score on a Tier-C ranking page is rare and worth investigating, and vice versa.
Calibration corpus: 200+ pages audited inside FORKOFF's AI-search-optimization engagement, scored against actual LLM citation outcomes at T+30, T+60, T+90. AEO snippet ownership (22%) and LLM citation surface (20%) are the highest-weight dimensions because they correlate strongest with citation lift. Schema (18%) sets the baseline. Linking (12%) is the lowest because well-cited pages survive on weaker internal linking.
Because citation surface is lagging: it reflects work done 30-90 days ago. Weighting it 100% would mean the audit can only diagnose pages that are already cited or already failing. The other five dimensions are leading indicators that move 4-8 weeks before the citation surface does, which makes the audit useful for pages that haven't been measured by LLMs yet.
The AEO Checker (/tools/aeo-checker) returns a 5-LLM scorecard for a brand + query set: citation share, snippet ownership, per-LLM presence. It's a brand-level surface measurement. The AI SEO Audit (this tool) is a single-page audit across six dimensions including LLM citation surface as one of them. Run AEO Checker for portfolio-level diagnosis; run AI SEO Audit for per-page fix-list.
No. Ahrefs / SEMrush audit rank + link profile + crawl. The AI SEO Audit covers the AI-search layer those tools don't measure. The recommended stack: Ahrefs / SEMrush for ongoing rank + link monitoring, AI SEO Audit at T+0 / T+30 / T+60 / T+90 for AI-search surface, AEO Checker for portfolio-level brand citation share.
Median accuracy +/- 8 points against the FORKOFF managed-engagement ledger. LLMs re-weight on a 4-8-week cycle, which means citation surface can shift after the audit runs: pages that were uncited can become cited, and vice versa. Treat the score as a 30-day directional estimate, not a real-time measurement.
Composite tier bands. Tier-A (75+) is cite-ready and defended. Tier-B (55-74) needs targeted lift on 1-2 dimensions. Tier-C (40-54) needs structural fixes on 2-3 dimensions. Tier-D (<40) is a rebuild candidate; restructure the page before re-auditing. The bands are calibrated against the FORKOFF managed corpus where Tier-A pages saw 3-9 LLM citations per query.
30-45 days for the surface dimensions (schema, snippet, answer-engine, freshness). 60-90 days for the LLM citation surface to re-weight. Pages that fix all surface dimensions on day 1 typically see 12-22 composite-point lift by T+45 and another 6-14 by T+90 as the citation surface catches up.
No. The audit runs against the public page surface (schema markup, on-page content, FAQ + HowTo structure, last-updated timestamps) and against public LLM responses on the target query set. No GSC, no analytics, no signup. The managed engagement (FORKOFF AI Search Optimization) plugs into your CRM + GSC for closed-loop measurement.
Yes. Same model. Run the same query set on a competitor URL to score the gap. The most valuable use is auditing the page that's currently ranking #1 (or being cited by ChatGPT) on your target query and using its dimension scores as the bar to clear.
The audit works on any language LLMs cite: major Romance + Germanic + East Asian + Arabic. The query set should match the page's language. Per-LLM coverage varies by language (Perplexity is strongest at non-English; Grok is weakest); the composite weights are calibrated against English and may shift +/- 10% for other languages.
The audit is the kickoff deliverable. Every FORKOFF AI Search Optimization engagement starts with a per-page audit across the top 20 commercial pages, which sets the baseline composite. The 90-day delivery program targets +20 composite points on the top 5 pages and +12 on the next 15. The free version exposes the model; the managed version applies it across a portfolio.
AEO is one of the six dimensions (snippet ownership). The audit covers the broader AI-search surface (Schema.org coverage, internal linking, answer-engine readiness, freshness + author signals) that AEO alone misses. AEO is a tactic; AI SEO is the page-level model.
Yes. No signup, no email gate. Run as many pages as you want. The managed FORKOFF AI Search Optimization engagement applies the model to your portfolio with weekly reporting + closed-loop citation tracking.
The managed engagement that takes the audit fix-list and runs it across a portfolio with weekly reporting + closed-loop citation tracking.
Brand-level 5-LLM scorecard. Where AI SEO Audit is per-page, AEO Checker is portfolio-wide citation share.
Per-post engagement quality audit. Same audit-ledger philosophy, applied to a single piece instead of a page.
Per-page AI-SEO audit · 6-dimension composite · prioritized fix-list · re-audit at T+30 / T+60 / T+90.
Run the audit
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