ai-visibility-audit

Installation
SKILL.md

AI Visibility Audit

Audit how a brand appears in a dated sample of AI answers and identify useful investigations. Connect through the unifapi skill. Read the current schema and price for each operation, set a budget, and reuse existing product context.

Workflow

  1. Choose 10–30 prompts covering definitions, comparisons, purchase criteria and concrete use cases. Freeze brands, aliases, citation domains, market and language.
  2. Use POST /geo/answers for ChatGPT or Gemini. Record engine, surface, exact prompt, search mode, reported model (or null), observation time, answer, sources, brand observations and request id. ChatGPT natural and forced-search samples belong in separate groups.
  3. Use /geo/serp for Google AI Mode and /seo/serp with include_ai_overview for Google Search AI Overviews. Inspect answer references; a top-level target match can also refer to another link. A result's rank is not a brand recommendation rank. Do not attribute either Google response to ChatGPT.
  4. Keep corpus discovery separate. /geo/mentions/search, /top-domains and /top-pages identify indexed answers and frequently represented sources. They do not confirm the result of a particular live prompt. /cross-aggregated-metrics returns group counts with potentially overlapping groups, not a computed citation share.
  5. Save raw normalized responses and billing. Use the runner in llm-mention-tracking/scripts/monitor.mjs for budgeted ChatGPT/Gemini collection, resumable snapshots and CSV evidence.

Measure coverage and tracked-brand share

Use the definitions in references/geo-methodology.md. Report completion rate, answer rate, brand mention coverage and citation coverage per engine. Coverage measures presence across successful collections, including valid no-answer results. Share measures a brand's fraction of the summed observations for tracked brands; it does not estimate total market share.

Do not merge citation links with unused search results. Deduplicate a brand within each answer. Missing denominators are N/A. If weighting by estimated AI search volume, show the unweighted result and use a denominator summed across every tracked brand. Never use an “any brand appeared” denominator and label the result share.

Investigate misses

Installs
29
GitHub Stars
559
First Seen
Jun 6, 2026
ai-visibility-audit — unifapi-agent/agents