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 audit the domain-level signals AI agents check before they trust your site: robots.txt 7-bot allowlist, llms.txt + llms-full.txt, .well-known/* manifests (MCP, Agent Skills, A2A, OAuth), sitemap.xml, and schema.org graph completeness. Domain-substrate audit, not per-page HTML signals, not per-LLM citation queries. Want page-level AEO signals instead? Use AEO Checker.
<iframe
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loading="lazy"
title="GEO Audit by FORKOFF"
></iframe>Paste into a Custom HTML block.
Use /embed and paste the iframe src URL.
Drop into an Embed element. Lazy-loaded by default.
Each engine has different ranking priors. Google AI Overview rewards Schema + freshness. Perplexity rewards authority. SearchGPT rewards source diversity. The audit scores presence per engine, weights by search-volume share, and surfaces source-set bias. Our breakdown of Perplexity vs Google AI Overviews walks through exactly where those two priors diverge. For how this generative surface differs from the answer-engine one, the AEO vs GEO guide maps the split by tactic and measurement. To see whether the brand is actually cited on your commercial queries across all five engines, run the AI visibility checker.
Weights are calibrated against 2026 search-volume share + click-flow attribution. Brands that index hard on Perplexity look strong on the per-engine bar but underweight in the composite. Google AI is the largest single share of where the buyer actually searches.
36
Median composite · un-optimized 2026 brands
120+
Brand audits in the calibration corpus
0-100 per engine. Below 30 on the highest-weight engine is the priority leak. Distribution across all 5 engines is more durable than concentration on one.
Lit cell = brand cited by that engine on that query. The matrix shows where the brand has earned position vs where the gap is concentrated.
Standard deviation of per-engine scores. High bias = concentrated on one engine, exposed to its re-weight cycle. Low bias = distributed, durable.
Surface moves at T+30. Engines re-weight 4-8 weeks later. Tier-D pages rebuild before re-auditing; Tier-C reach Tier-B at T+60 with the right lift plan.
Inputs
Brand domain. The root domain to audit. Subdomain-level audits (blog.brand.com vs brand.com) run separately because generative engines treat them as different sources.
Commercial query set. 10-25 queries the brand wants to surface on. Question-form + comparison + how-to queries land the highest generative-engine credit.
Optional · target geo. US default. Audit can run on UK, EU, IN, BR locales because generative engines surface different sources by geo.
Outputs
Per-engine presence (0-100). Five numbers: Google AI Overview · Bing Copilot · SearchGPT · Perplexity · You.com. Each rolls up cited + mentioned + absent across the query set.
Composite score + source-set bias. Composite is weighted across engines. Bias = standard deviation of per-engine scores; high bias means concentrated citations on one engine, low bias means distributed.
Per-engine lift plan. Each engine has different priors. Plan names the highest-leverage move per engine for the largest composite lift.
GEO audits the agent-readiness substrate of a domain: the robots.txt 7-bot allowlist, llms.txt + llms-full.txt, the four AI-agent manifests in /.well-known/, sitemap hygiene, and schema.org graph signal. These are the primitives every generative engine and AI agent reads BEFORE deciding whether your site is even citable. The audit returns a per-dimension score, a weighted composite (0-100), and a prioritized lift plan. Different from AEO Checker (page-level HTML signal scorecard) and AI Search Visibility Checker (LLM citation prevalence test) - this is the underlying agent-substrate layer.
Each card is a real audit cell from the FORKOFF managed-engagement ledger. Run the live tool above on your own brand to score it.
Scenario 01
Tier-CAI agency · pre-GEO
Established agency ranking #6 on Google for primary commercial query. Cited by Perplexity on 3 of 15 queries; absent from Google AI Overview entirely.
Composite
32
Recommendation
Top priority is Google AI Overview (32% weight). Add HowTo + FAQPage schema, earn 3 inbound links from .edu / .gov / Wikipedia adjacency. Re-audit at T+45.
Scenario 02
Tier-CWeb3 protocol comparison page
Comparison page cited by Perplexity + SearchGPT, absent from Google AI Overview, weak Bing presence.
Composite
48
Recommendation
Strong long-tail engine fit. Strengthen Schema + freshness signals to land Google AI Overview. The 32% weight gain is the largest unlock.
Scenario 03
Tier-DPre-launch SaaS
New domain, no rankings, full schema. Zero generative-engine surface. Brand mentions across 1 of 25 queries.
Composite
12
Recommendation
Tier-D = pre-engine. Build authority signals (case studies, primary research, citations from cited domains) before re-auditing. Pre-launch GEO is rebuild, not optimization.
Scenario 04
Tier-AFORKOFF · baseline
forkoff.xyz · 25 commercial queries · cited on 18 by Perplexity, 14 by SearchGPT, 9 by Google AI, 12 by Bing.
Composite
72
Recommendation
Defend. Push Google AI presence above 75 by earning 3 more inbound links from .edu adjacency. Re-audit quarterly.
Rank trackers measure position #1-10 on the classic blue-link SERP. They are blind to the AI Overview that paraphrases the answer without sending the click. GEO Audit covers that surface.
← scroll horizontally to see more →
| Feature | FORKOFF GEO Audit5-engine generative-SERP audit + per-engine lift plan | Rank trackersAhrefs · SEMrush · STAT · classic SERP rank tracking | AEO CheckersChatbot citation share (5-LLM) | AI SEO AuditsPer-page 6-dimension AI-native audit |
|---|---|---|---|---|
| Measures Google AI Overview presence | partial | |||
| Tracks Bing Copilot + SearchGPT + You.com | partial | |||
| Returns per-engine lift plan with prioritized moves | partial | |||
| Surfaces source-set bias (concentration vs distribution) | ||||
| Free, no signup, no domain claim | ||||
| Best for classic SERP rank monitoring | partial | |||
| Best for chatbot citation share monitoring | 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
Generative Engine Optimization audit. Measures whether a brand surfaces as a cited source across the 5 generative-SERP engines (Google AI Overview, Bing Copilot, SearchGPT, Perplexity, You.com) on a target commercial query set. Returns per-engine presence, weighted composite, source-set bias, and a per-engine lift plan.
SEO targets classic SERP rank position (#1-10 blue links). AEO (Answer Engine Optimization) targets chatbot citations (ChatGPT, Claude, Gemini, Grok). GEO targets the generative-SERP layer, the AI-synthesized answer at the top of search results, with cited sources. SEO is rank, AEO is chatbot, GEO is search-engine-generative. The three are complementary; a healthy 2026 brand scores in all three.
Because it sits on the highest-traffic generative surface in 2026. Google AI Overview shows on roughly 30% of commercial-intent queries in the US (rising) and consumes 60% of the click volume those queries used to send to organic results. Missing the AI Overview means missing the buyer at the moment of intent. The 32% weight is calibrated against managed-engagement attribution data on the FORKOFF ledger.
Standard deviation of per-engine presence scores. High bias = brand cited heavily on one engine (e.g., Perplexity) but absent on others. Low bias = distributed across engines. Distribution is more durable because each engine has different ranking priors; concentration leaves the brand exposed to one engine's algorithm change.
AI SEO Audit (/tools/ai-seo-audit-free) is per-page across 6 surface dimensions (Schema, snippet, citations, linking, answers, freshness). GEO Audit is per-brand across 5 generative engines. AI SEO is the page-level fix-list; GEO is the engine-level surface measurement. Run AI SEO on your top 20 commercial pages; run GEO on the brand-level query set.
Because Claude + Gemini are chatbot products, not search engines. They surface in the AEO Checker tool (/tools/aeo-checker) which scores chatbot citation share. GEO covers the search-engine-generative surface specifically: Google + Bing + SearchGPT (ChatGPT browse mode) + Perplexity + You.com. Different products, different priors, different audit.
Median accuracy +/- 6 points against the FORKOFF managed-engagement ledger (n=120 audits, 18-month rolling window). Generative engines re-weight on 4-8-week cycles, which means scores can shift +/- 10 points between audits. Treat the score as a 30-day directional estimate.
Per-engine, ordered by composite-lift-per-effort. Example: '+9 Google AI: Add FAQPage + HowTo schema, earn 3 inbound from .edu adjacency. +5 Perplexity: Strengthen primary-source citations on top 5 pages. +3 SearchGPT: Add source diversity via X + LinkedIn references.' Each move names the engine, the change, and the projected composite lift.
30-60 days for surface moves (schema, citations, freshness). 60-120 days for the engine to re-weight and surface the brand. Brands that work the top 3 lift-plan moves typically see +10 to +18 composite points by T+60 and another +5 to +10 by T+120.
No. The audit runs against public engine 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, swap the domain. Useful for: identifying which engines a competitor is winning + which queries are uncontested + what schema or citation pattern correlates with their composite.
The audit is the kickoff deliverable. Every FORKOFF AI Search Optimization engagement starts with a baseline GEO audit + a per-page AI SEO audit on the top 20 commercial pages. The 90-day delivery program targets +20 composite points on GEO and Tier-A on the top 5 pages. The free version exposes the model; the managed version applies it.
Yes. No signup, no email gate. Run as many brand audits 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 GEO audit + AI SEO audit and runs them across the portfolio with weekly reporting.
Per-page 6-dimension AI-native audit. Where GEO is brand-level engine surface, AI SEO Audit is page-level fix-list.
Brand-level 5-LLM chatbot citation share. GEO covers the search-engine-generative layer; AEO covers the chatbot layer.
Generate the structured-data blocks that earn the citations the GEO audit measures. 8 schema types covered (FAQPage, Article, Dataset, Organization, more).
Sister tool. 5-engine LLM citation audit with Discovery Gap diagnosis (branded vs head-term split).
Per-post engagement quality audit. Same audit-ledger philosophy applied to a single piece of content.
5-engine generative audit · weighted composite · per-engine lift plan · re-audit at T+30 / T+60 / T+120.
Run the audit
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