Commerce · Component · ai-search-visibility-probes
AI-answer visibility probing and content-gap analysis
What it does
Run multilingual prompt batches and aggregate predicted brand recommendations, citations, displacement and content actions.
Core pattern
Batched question probes + citation and mention counts
- Input
- Travel questions and tracked brand
- Output
- Observation records, citation/coverage slices and action backlog
Key parameters
| Name | Type | Default | Values |
|---|---|---|---|
| prompt_registry | — | — | — |
| target_engine_style | — | — | — |
| market | — | — | — |
| intent | — | — | — |
| run_date | — | — | — |
Maturity and limits
Persisted runs/observations and batch service exist; source explicitly emulates some named answer-engine styles. Static source inspection only; no runtime, provider, deployment or test-pass claim.
config with credentials present. No root reuse license found; external content/platform terms and internal hotel/business data access constrain reuse. Perplexity/Copilot labels do not prove direct access to those engines; outputs may be simulated/model-inferred.
Used in pipelines
Industry tags
- Travel & hotelsSource-supported industry
For work involving destinations, room rates and bookings, use batched question probes followed by citation and mention counts.
- EducationTransferable use
For reviewing the performance of adult-course information content, use batched question probes followed by citation and mention counts.
- Media & contentTransferable use
Support “Check content performance and gaps” with batched question probes followed by citation and mention counts.
Skills pack
Contract scaffold and deterministic mock
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