Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
- Added "curl" and "jq" as required system binaries in the skill metadata. - No other user-facing documentation or usage changes.
What This Skill Does
Searches for real-world locations using natural language queries via the Camino AI API. Returns place results with coordinates, distances, relevance scores, and optional AI-generated summaries. Supports filtering by radius, pagination, and historical data.
Natural language input with automatic coordinate generation means you can search without knowing exact lat/lon for well-known locations.
When to use it
- Finding coffee shops near a specific landmark
- Locating Italian restaurants within walking distance
- Searching for brunch spots in a neighborhood
- Looking up historical place data from a past date
- Getting a ranked list of quiet workspaces with wifi
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Find quiet coffee shops with wifi near Times Square
- 1Calls query.sh with the natural language query and Times Square as location
- 2API auto-generates coordinates for Times Square
- 3Returns ranked results with relevance scores and distances
- 4Requests answer:true to get a human-readable summary
A ranked list of cafes with coordinates, distances, and a summary like "I found several quiet coffee shops with wifi near Times Square..."
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.