| name | ai-answer-gap |
| description | When the user wants to find the prompts where their brand should be cited in AI answers but isn't — and who owns the answer instead — prioritized by AI search volume so content can attack the biggest gaps first. Also use on "AI answer gap," "AI content gap," "where am I missing from AI answers," "what prompts am I losing in AI," "GEO content gaps," "prompts I should own but don't," or "find my AI visibility gaps." For the full diagnostic audit, see ai-visibility-audit. For ongoing tracking, see llm-mention-tracking. |
| license | MIT |
| metadata | {"author":"UnifAPI","version":"1.1.0"} |
AI Answer Gap
Turn observed AI-answer gaps into a prioritized research and content backlog. Use an existing ai-visibility-audit or collect a dated panel first. Read available product context so proposed topics match what the product can credibly help with.
Use UnifAPI for live evidence
Connect with the unifapi skill to discover current schemas, prices and authentication before collecting data.
Workflow
- Select relevant prompts. Group them by use case and search intent.
/geo/keywords/search-volume supplies optional demand estimates; an absent estimate is unknown, not evidence that a useful niche prompt has no value.
- Check current answers. Use
/geo/answers for ChatGPT/Gemini, /geo/serp for Google AI Mode, and /seo/serp with include_ai_overview for Google Search AI Overviews. Keep engines, markets and natural/forced-search settings separate. Preserve exact answers and cited source URLs.
- Describe the observed gap. Distinguish no answer, unsuccessful collection, brand absent from this answer, name-only mention, and cited brand. A sample is not proof of universal absence. Inspect references; top-level
is_target and unused search results do not by themselves establish a citation.
- Research sources. Open the actual cited pages.
/geo/mentions/top-pages, /top-domains, and /search add separate indexed-corpus context. They do not supply the winning URL for a particular live prompt. /cross-aggregated-metrics gives group counts, not ownership of your prompt-panel gaps.
- Propose a response. Identify the missing information, evidence or third-party representation. Choose an existing-page update, a new useful page, or an external research lead. Each proposed change needs a concrete source and a plausible benefit to readers. Name-only mentions and existing organic rankings are clues, not proof that formatting is the cause.
- Prioritize. Consider product relevance, evidence of demand, gap quality, available expertise, and effort. Show the inputs and uncertainty. Optional scoring is a planning aid, not a predicted citation lift.
- Validate later. Use the same panel and multiple dated runs after changes. Compare paired successful samples, show completion/answer rates, and avoid attributing every change to the edit.
Output
For each priority, give the exact prompt, engine/configuration, observed brand status, cited competitors or sources, suggested page/action, evidence, effort estimate and a validation plan. Preserve request ids and billed credits. An API failure should appear as missing evidence and never as a content gap.
See the audit methodology for coverage/share definitions, citation counting and evidence boundaries. Use llm-mention-tracking for budgeted snapshots and changes over time. This skill researches and drafts; it does not publish content or send outreach without authorization.
