Which queries should I probe my brand against?

Five high-intent commercial queries that buyers in your category actually run. Mix three head-term queries (e.g. 'best web3 marketing agency') with two long-tail intent queries (e.g. 'fractional CMO for pre-Series-B AI startup'). The visibility distribution across head vs long-tail is more informative than either alone; head-term hits prove brand recall, long-tail hits prove specific-intent fit.

Does the tool work for AI startups, Web3 protocols, or both?

Both. The methodology is identical; only the query set differs. AI startups probe queries like 'best AI marketing agency', 'top AI tool for X', 'AI SDR alternatives'. Web3 protocols probe 'best web3 marketing agency', 'top crypto launch agency', 'KOL marketing for token launch'. The audit ledger that backs the tool is calibrated against 200+ FORKOFF campaigns split across both lanes.

Tool · AI search visibility

Is your brand cited by ChatGPT, Perplexity, and Claude?

Probe 5 commercial queries across 3 LLMs in one pass. Get a citation map, sentiment classification, and a 90-day Generative Engine Optimization sprint recommendation calibrated against the FORKOFF qualified-view bench.

Outcome-priced · audit ledger weekly · AI + Web3 lanes both supported

▸ The wedge

Most SEO tools tell you Google's answer. Most LLM trackers stop at one model. FORKOFF probes the citation graph all three retrieve from.

How the checker works

Probe. Score.
Recommend.

Three steps tied to the same audit-ledger methodology that runs every FORKOFF qualified-view campaign. Same bench across AI startups and Web3 protocols.

01Probe

Run 5 queries × 3 LLMs in one pass.

ChatGPT, Perplexity, Claude. Five high-intent commercial queries you actually care about. The probe captures the full natural-language response, not just an embedded citation list.

Query × LLM pairs per check.

02Score

Per-citation position + sentiment classification.

For each pair: was the brand cited, in what position relative to competitors, what was said about it, and is the sentiment positive, neutral, negative, or absent. Visibility score 0-100 + grade band.

0-100

Visibility score across all probes.

03Recommend

90-day GEO sprint anchored on absent queries.

Output a concrete sprint: which directory listings to target, which parasite hosts to publish on, which comparison pages to ship, which schema gaps to close. Outcome-priced execution with weekly citation-lift reporting.

90 days

Default sprint window. Calibrated, not estimated.

Why it matters · 2026

Eight in ten buyers now ask an LLM before they Google.

The first research pass for any commercial query has shifted from a search engine to a chat interface. ChatGPT, Perplexity, and Claude do not surface ten blue links. They synthesize an answer and cite a small set of sources. If the brand is not in that cited source set, the buyer never sees it.

This is a different surface from Google SEO. LLMs ground answers on a different citation graph: directories, listicles, comparison pages, parasite SEO posts, structured FAQ schema, third-party endorsements. A brand can rank position one on Google and still be functionally invisible in ChatGPT. The checker is the read tool for that surface; Generative Engine Optimization is the write tool.

forkoff.xyz dog-foods this. Self-audit 2026-05-04: 3 LLM hits across 24 commercial queries. Outcome-priced GEO sprint kicked off the same week.

Comparison

AI search visibility vs SEO audit vs manual spot-check.

Three ways to read your brand's surface. Only one ties the read to a write surface (Generative Engine Optimization) anchored on outcome-priced execution and a weekly citation-lift ledger.

Feature	FORKOFF AI Search VisibilityCitation map · sentiment · GEO recommendation	Generic SEO audit toolBacklinks · on-page · SERP rank	Manual ChatGPT spot-checkFree · ad-hoc · no benchmark
Probes ChatGPT, Perplexity, Claude	Yes, all three	No (Google only)	Manual, one at a time
Citation position scoring	Yes, per-query position rank	N/A	Eye-balled
Sentiment classification	positive / neutral / negative / absent	No	No
GEO sprint recommendation	Yes, anchored on absent queries	No	No
Audit ledger benchmark	FORKOFF qualified-view bench	N/A	N/A
Pricing	Free v1 demo, audit by application	$99-499/mo SaaS	Free, your time
Outcome-priced execution path	Yes, weekly citation-lift ledger	No	No

FAQ

AI search visibility, methodology, and the GEO sprint.

It probes a brand against ChatGPT, Perplexity, and Claude on 5 high-intent commercial queries (e.g. 'best AI marketing agency', 'top GEO agency 2026'). For each query × LLM pair, it records whether the brand was cited, in what position, what was said about it, and the sentiment of the mention. The tool then aggregates the results into a visibility score (0-100), a grade band, and a 90-day GEO sprint recommendation tied to the queries where the brand is absent.

80% of buyers now ask an LLM before they Google. If your brand does not surface in the cited source set when ChatGPT, Claude, or Perplexity answer your category's commercial queries, you are functionally invisible to the buyer's first research pass. SEO traffic to your owned site does not necessarily translate; LLMs ground their answers on a different citation graph (directories, listicles, comparison pages, parasite SEO, structured Q&A). Tracking this surface is the new search console.

No. A Google SEO audit looks at on-page signals, backlinks, Core Web Vitals, and how Googlebot ranks pages. The AI visibility checker looks at whether the brand is cited inside the natural-language responses LLMs generate, which is a different end surface. The two surfaces overlap (good schema and authoritative content help both) but a brand can rank #1 on Google and still be invisible in ChatGPT, and vice versa. Run both audits, then compare the gap.

v1 ships a static sample report so the pillar surface, education, and methodology are public. The live ChatGPT + Perplexity + Claude API pass is in private beta; access is gated to applicants with a real audit project to anchor the calls against. This avoids burning API budget on idle tire-kickers and keeps the tool calibrated against the FORKOFF qualified-view bench. Apply for access via the CTA below.

Low visibility (under 50) means the citation graph LLMs retrieve from does not yet recognize the brand as a credible answer for the queries you care about. The fix is engineering the corpus those models retrieve: directory listings (G2, Capterra, Clutch), parasite SEO ladder (Medium, dev.to, HackerNoon), comparison pages, listicle inclusion, schema validity, and authoritative third-party citations. FORKOFF runs this as a 90-day Generative Engine Optimization sprint, outcome-priced and tracked against weekly citation lift on the same query set.

Related FORKOFF surfaces

The services the toolmaps onto.

01 / 04Open

GEO Agency

The 90-day Generative Engine Optimization sprint the tool maps onto. Outcome-priced, audit-ledger tracked.

02 / 04Open

LLM SEO

Corpus engineering for the retrieval graph that ChatGPT, Claude, Perplexity, and Gemini ground their answers on.

03 / 04Open

ChatGPT SEO

Specific to the ChatGPT citation graph: directory + listicle + canonical Q&A engineering.

04 / 04Open

Perplexity SEO

Perplexity's retrieval bias is different. Freshness + authoritative source domains. Different play.

The brand line

Stop guessing your AI surface. Apply for a real audit.

Outcome-priced execution · audit ledger entry per shipped phase · BY APPLICATION · five GEO engagements per quarter across AI + Web3.

Apply for the audit

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