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 binaries in the skill's metadata. - No functional or usage changes; documentation now explicitly lists binary dependencies.
What This Skill Does
Evaluates any address or coordinates for home buyers and renters by pulling nearby schools, transit stops, grocery stores, parks, restaurants, and walkability data via the Camino AI API. Takes a street address or lat/lon pair and returns a structured summary of the surrounding area within a configurable radius.
Combines geocoding, place search, and area context into a single API call instead of manually cross-referencing maps, school databases, and transit tools.
When to use it
- Checking school options near a house you're considering buying
- Comparing walkability of two rental apartments before signing a lease
- Researching transit access around a new neighborhood
- Scoping grocery and park availability before relocating
- Quickly profiling an unfamiliar area before a property visit
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: evaluate 350 Fifth Avenue, New York, NY for walkability and nearby schools
- 1Geocode the address using the Camino AI query endpoint
- 2Send a context request with real estate focus parameters and a 500m urban radius
- 3Parse the response for schools, transit, grocery, parks, and restaurants
- 4Summarize area_description and context_insights for the user
Area summary listing nearby schools, transit stops within 500m, grocery options, parks, and a walkability assessment for the address
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.