AI Search Prompt Generator: GEO & AEO Prompt Sets for Brand Tracking

No API key required. Generate the prompt set your brand should actually be tracked on in ChatGPT, Perplexity, Gemini and Google AI Overviews — the questions real buyers type, stratified across the five intents that decide whether a visibility measurement is representative or just a narrow slice of one surface.

This is the step before measurement. Every AI visibility tool asks you for prompts. Almost nobody tells you which prompts to use, and a bad prompt set produces a confident number about nothing.

For generative engine optimization (GEO), answer engine optimization (AEO) and LLM SEO work: AI search prompt research, GEO prompt ideas, AEO query sets, brand tracking prompts and competitor comparison queries.

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Why the prompt set decides the measurement

A prompt set made only of "best X tools" queries measures one commercial surface, and it is the surface where every competitor is already looking. The questions that decide a purchase are spread across the funnel, and three of them will never appear in a "best X" list:

• Someone researching the category before they know any vendor names.
• Someone checking whether you are legitimate after a colleague named you.
• Someone comparing you head to head with one named rival.

Measure only the first kind and you get a number that is real but answers a question nobody asked.

The five intents

Intent	What it captures	Names your brand?
Commercial	"best X for Y", "top X in	No
Informational	how / what / why questions about the category	No
Transactional	pricing, plans, trials, "how much does X cost"	No
Brand-defensive	reviews, legitimacy, pros and cons, "alternatives to X"	Yes
Comparison	"X vs Y: which is better" against a named competitor	Yes

The split matters for interpretation, not just coverage. Commercial, informational and transactional prompts deliberately do not name your brand: if they did, the measurement would be circular — you would be asking the engine about a brand you just handed it, then congratulating yourself when it comes up. Those three measure unprompted discovery. Brand-defensive and comparison prompts name your brand on purpose, and measure reputation instead. They are different questions, and a prompt set that blends them without saying so produces a mention rate that means neither.

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Quick start

The only required field is brand.

{
    "brand": "Notion"
}

A fuller set, which is what you want before a first audit:

{
    "brand": "Notion",
    "industry": "team workspace and note-taking software",
    "competitors": ["Coda", "Airtable", "ClickUp"],
    "market": "US",
    "language": "en",
    "maxPrompts": 20
}

Runs in well under a minute. The output is one dataset row per prompt, ready to paste straight into a tracker.

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What you get

One row per prompt:

Field	What it is
index	Position in the set
prompt	The question itself, in your chosen language
intent	commercial, informational, transactional, brand_defensive, comparison
brand	The brand the set was built for
competitors	Competitors supplied, used by the comparison prompts
industry	Category, as supplied or inferred
market	Two-letter country code
language	Language the prompts are written in
origin	generated by the model, or fallback if generation was unavailable
generatedAt	ISO timestamp

A SUMMARY record in the key-value store carries the totals, the per-intent breakdown and any warnings.

Example output

[
    {
        "index": 0,
        "prompt": "What are the best team workspace and note-taking tools for a remote US team?",
        "intent": "commercial",
        "brand": "Notion",
        "market": "US",
        "language": "en",
        "origin": "generated"
    },
    {
        "index": 3,
        "prompt": "What are the best alternatives to Notion?",
        "intent": "brand_defensive",
        "brand": "Notion",
        "market": "US",
        "language": "en",
        "origin": "generated"
    }
]

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Input reference

Field	Type	Default	Description
brand	string	—	Required. The brand the set is built around.
industry	string	""	Category buyers search in. Empty lets the model infer it.
competitors	string[]	[]	Named competitors, used by the comparison prompts.
language	string	"en"	Language the prompts are written in.
market	string	"US"	Two-letter country code, used where a question carries a location.
maxPrompts	integer	20	How many prompts to generate (1–100), spread evenly across the chosen intents.
intents	string[]	all five	Which intents to cover.
openRouterApiKey	string (secret)	""	Optional. Generation runs on an included key by default.
model	string	openai/gpt-5.6-luna	Any OpenRouter model ID when you supply your own key.

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Then measure them

A prompt set is an input, not an answer. To find out how AI answer engines actually respond to these prompts — mention rate, position, sentiment, share of voice against your competitors, and what moved since last week — feed them to the tracker:

AI Search Visibility Tracker: ChatGPT, Perplexity & Gemini

Paste this Actor's prompt column into its queries field and it skips its own generation step and uses yours verbatim. It asks each prompt several times per engine, because AI answers are non-deterministic — on a real 40-answer run, one prompt came back 4/5, 4/5, 1/5 and 0/5 across four engines, a true mention rate of 45% that no single-sample audit can even represent.

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Pricing

Pay per event, no subscription:

Plan	Per prompt	A 20-prompt set
Free	$0.005	$0.10
Bronze (Starter)	$0.004	$0.08
Silver (Scale)	$0.0035	$0.07
Gold (Business)	$0.003	$0.06

Charged only for prompts actually written to the dataset — a run that returns nothing is not charged. Plus Apify's standard start event at $0.00005.

For comparison, the closest comparable Actors on Apify Store charge $0.03 and $0.05 per prompt, which is $0.60 and $1.00 for the same 20-prompt set.

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Run it unattended

Pay-per-event pricing and limited permissions make this callable from an agent with nothing to configure. Connect it to any MCP client:

https://mcp.apify.com?tools=emoubarak/ai-search-prompt-generator

Then ask your agent: "Build me a GEO prompt set for [brand] in [market], then track it."

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FAQ

What is a GEO prompt set?

The list of questions you measure a brand's AI search visibility against. Generative engine optimization is measured by asking answer engines real buyer questions and recording whether your brand appears; the prompt set is what you ask. Its coverage decides what your numbers can and cannot tell you.

How many prompts do I need?

Ten is enough to see whether a brand appears at all. Twenty across five intents is a solid first audit. Past forty you are usually adding near-duplicates that inflate cost without widening coverage — the generator de-duplicates, but it cannot invent distinct buyer intent that does not exist in a narrow category.

Why don't the commercial prompts mention my brand?

Because naming your brand in the question guarantees it appears in the answer. That measures nothing. Unprompted discovery — does the engine bring you up on its own — is the metric worth tracking, and it requires questions that do not hand the engine the answer.

Can I use these prompts with another tool?

Yes. The output is plain text with an intent label; nothing about it is specific to any tracker. Export as CSV or JSON from the dataset.

Does it work in languages other than English?

Yes. Set language and the prompts are written in that language. Write them in the language your customers actually search in, not your reporting language — an English prompt set measures English-language AI answers regardless of the market you set.

What happens if the model is unavailable?

The run still succeeds and returns a built-in stratified set derived from your brand, category and competitors, with a warning and origin: "fallback" on every row. A generic set is still usable; an aborted run is not.

Is this the same as keyword research?

No, and the difference matters. Keyword research finds strings people type into a search box, ranked by volume. This produces questions people ask an assistant in natural language — longer, more conversational, and frequently with no search volume at all attached to them, because they were never typed into Google in that form.

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License

MIT.