places

What This Skill Does

The places skill is a powerful location intelligence tool designed to bridge the gap between human-readable addresses and machine-readable geographic coordinates. At its core, the skill provides a robust interface for geocoding—the process of converting street addresses into latitude and longitude—as well as reverse-geocoding and landmark discovery. Unlike simple search tools, places offers granular control, allowing you to pass structured data like specific street names, cities, and countries, or free-form queries for general points of interest. A standout feature is the optional inclusion of street-level imagery, which provides visual context alongside precise geographic data. This makes it an essential utility for developers building map-based applications, logistics trackers, or automated travel planning assistants.

Installation

Installation is streamlined through the OpenClaw ecosystem. You can install the skill globally via npx from the Camino AI repository:

npx skills add https://github.com/barneyjm/camino-skills --skill places

Alternatively, for those using clawhub, a simple npx clawhub@latest install places will handle the dependencies. After installation, ensure your CAMINO_API_KEY is correctly defined in your ~/.claude/settings.json file under the env block to enable authenticated requests to the Camino API. If you are just testing, you can obtain a temporary trial key via the /trial/start endpoint.

Use Cases

• Geocoding: Automatically converting customer shipping addresses into coordinates for delivery routing.
• POI Discovery: Finding the exact location of landmarks, tourist attractions, or specific businesses for travel itineraries.
• Visual Verification: Using the include_photos parameter to retrieve street-level visual data, helping users verify if an address matches their visual expectations.
• Address Normalization: Providing structured parameters to clean up messy, user-inputted address strings into valid, standardized formats.

Example Prompts

1. "Find the exact coordinates and street-level photo for the Louvre Museum in Paris."
2. "Locate the address for 10 Downing Street, London, and return it in a structured format."
3. "Search for the top 3 hotels near the Eiffel Tower and provide their addresses."

Tips & Limitations

• Precision: When using structured parameters (street, city, state), the returned data is significantly more accurate than using free-form text. Use structure whenever possible.
• Performance: For high-volume lookups, ensure you are utilizing the API limits appropriately, as the trial key is limited to 25 calls.
• Distinction: Remember that places is for specific coordinate and address lookup, while the query skill should be used for subjective or broad natural language requests (e.g., 'find a quiet cafe'). Avoid using places for ambiguous, opinion-based searches as it may return empty results.