Free tool - no login
AI Prompt Gap Finder
See the buyer-intent prompts AI assistants answer about your category - the questions where you either show up or a competitor does. Enter your domain to get the prompt battery the audit scores you against.
There is no search-volume data for AI prompts, so tracking starts from intent, not keywords. A working set is 20 to 40 prompts spanning six angles - category best-of, comparisons, alternatives, use cases, personas, and objections - run repeatedly, because engines answer the same prompt differently across runs. This tool builds that battery for your domain.
Free and instant. No crawl, no login. Generated from your brand and category.
Which prompts should I track for AI visibility?
Cover six angles: category best-of (best X for Y), head-to-head comparisons (A vs B), alternatives (alternatives to A), use cases (how do I do Z with X), personas (best X for a team like mine), and objections (is X worth it, is X too expensive).
The angles matter more than the exact wording. People type long, specific questions into AI assistants, and the answer either includes your brand or it does not - there is no page two to fall back to.
How many prompts do I actually need?
A representative 20 to 40 covering your core topics, personas, and journey stages beats hundreds of near-duplicates. Engines split prompts into sub-queries during retrieval, so slight phrasing changes often land in the same place.
Spend the saved attention on re-runs instead: repeated sampling of a tight set produces trend data a bloated list never will.
These are the questions. The free audit runs them across ChatGPT, Claude, Perplexity, Gemini, and Google AI - and shows, cell by cell, where you are cited and who is cited instead.
Why do ChatGPT answers change every time I ask?
Sampling temperature, model routing, and live retrieval all introduce variance, so a single check proves an instant, never a trend. If your brand appears in some runs and not others, your presence is a rate - and rates only mean something against a fixed baseline.
Scheduled re-tests against a baseline are what the Proof Loop automates - see how proof tracking works.
Awareness, consideration, decision: why the stage matters
The same category surfaces at every stage of a buyer's journey. Consideration prompts - shortlists and comparisons - most directly shape vendor selection, while objection prompts reveal the doubts engines repeat about you before a buyer ever reaches your site.
Tracking without stage context measures visibility without knowing what it influences.
What this tool does not do
It generates the questions; it does not ask them.
The free audit asks all of them across five engines, stores every answer as evidence, and turns each miss into a classified gap with a concrete fix path.
Frequently asked questions
Is there search-volume data for AI prompts?
No public volume data exists the way it does for keywords. Track topics and intent patterns instead of exact strings - engines decompose questions into sub-queries anyway, so wording variants often converge on similar answers.
Should I track branded prompts?
Yes, but the growth is elsewhere. The most valuable losses happen on non-branded category, comparison, and alternative prompts - the questions where shortlists form and your name never appears in the prompt.
How often should prompts be re-run?
On a schedule, not once. Answers vary between runs, so presence is a rate rather than a yes-or-no, and a stretch of repeated runs is what separates signal from noise.
Do different engines need different prompt sets?
Same battery, different results. Engines source differently - so run one representative set across several engines and compare where each cites you.
What do I do with a gap once I find it?
Ship a targeted change and re-test the same prompt against the pre-ship baseline. That close-the-loop step is exactly what the Fix Engine and Proof Loop automate.
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