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Readme & install
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Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill openclaw/skills --skill camino-places- _meta.json295 B
- SKILL.md5.3 KB
Overview
This skill locates places using flexible queries: free-form search or structured address components. It returns coordinates, standardized addresses, place types, relevance scores, and optional street-level photos. Use it for geocoding, named-place lookup, or retrieving visual context for map features.
How this skill works
Send either a free-form query (e.g., "Eiffel Tower") or one or more structured address fields (street, city, state, postalcode). The service searches geospatial indices and returns matching places with lat/lon, display names, address breakdowns, type and importance. Optionally include street-level imagery and control search depth via a basic/advanced mode and result limits.
When to use it
- Geocode a postal address into precise coordinates for mapping or routing
- Find a specific landmark, business, or POI by name
- Retrieve street-level photos to validate appearance or orientation
- Batch-lookup places from forms or datasets for enrichment
- Limit results or radius when you need nearby photos or local context
Best practices
- Use structured address fields for precise geocoding and fewer false positives
- Use free-form query for well-known landmarks and POIs
- Enable include_photos only when visual context is needed to save bandwidth
- Set limit between 1–50 to control response size and performance
- Use mode: "advanced" when you want richer, web-enriched place metadata
Example use cases
- Convert street addresses into coordinates for a delivery app
- Locate a named attraction and fetch nearby street-level photos for a travel guide
- Verify business locations returned from user input before displaying them
- Search by postal code to populate neighborhood results in a real-estate app
- Run bulk place lookups to enrich an archive of historical listings
FAQ
No. Either a free-form query or at least one structured address component is required; full addresses give the most precise geocoding.
How do I request street-level imagery?
Set include_photos to true and optionally adjust photo_radius (10–500 meters) to control which nearby images are returned.