| name | real-estate |
| description | Evaluate any address for home buyers and renters. Get nearby schools, transit, grocery stores, parks, restaurants, and walkability using Camino AI's location intelligence. |
| metadata | {"clawdbot":{"emoji":"🏠","requires":{"env":["CAMINO_API_KEY"],"binaries":["curl","jq"]},"primaryEnv":"CAMINO_API_KEY"}} |
Installation
Companion Skills: This is part of the Camino AI location intelligence suite. Install all available skills (query, places, relationship, context, route, journey, real-estate, hotel-finder, ev-charger, school-finder, parking-finder, fitness-finder, safety-checker, travel-planner) for comprehensive coverage.
npx skills add https://github.com/barneyjm/camino-skills
npx skills add https://github.com/barneyjm/camino-skills --skill real-estate
Via clawhub:
npx clawhub@latest install real-estate
Real Estate Scout
Evaluate any address or location for home buyers and renters. Combines location context analysis with targeted amenity searches to surface nearby schools, transit, grocery stores, parks, restaurants, and walkability insights.
Setup
Instant Trial (no signup required): Get a temporary API key with 25 calls:
curl -s -X POST -H "Content-Type: application/json" \
-d '{"email": "you@example.com"}' \
https://api.getcamino.ai/trial/start
Returns: {"api_key": "camino-xxx...", "calls_remaining": 25, ...}
For 1,000 free calls/month, sign up at https://app.getcamino.ai/skills/activate.
Add your key to Claude Code:
Add to your ~/.claude/settings.json:
{
"env": {
"CAMINO_API_KEY": "your-api-key-here"
}
}
Restart Claude Code.
Usage
Via Shell Script
./scripts/real-estate.sh '{"address": "742 Evergreen Terrace, Springfield", "radius": 1000}'
./scripts/real-estate.sh '{"location": {"lat": 40.7589, "lon": -73.9851}, "radius": 1500}'
./scripts/real-estate.sh '{"address": "350 Fifth Avenue, New York, NY", "radius": 500}'
Via curl
curl -H "X-API-Key: $CAMINO_API_KEY" \
"https://api.getcamino.ai/query?query=742+Evergreen+Terrace+Springfield&limit=1"
curl -X POST -H "X-API-Key: $CAMINO_API_KEY" \
-H "Content-Type: application/json" \
-d '{"location": {"lat": 40.7589, "lon": -73.9851}, "radius": 1000, "context": "real estate evaluation: schools, transit, grocery, parks, restaurants, walkability"}' \
"https://api.getcamino.ai/context"
Parameters
| Parameter | Type | Required | Default | Description |
|---|
| address | string | No* | - | Street address to evaluate (geocoded automatically) |
| location | object | No* | - | Coordinate with lat/lon to evaluate |
| radius | int | No | 1000 | Search radius in meters around the location |
*Either address or location is required.
Response Format
{
"area_description": "Residential neighborhood in Midtown Manhattan with excellent transit access...",
"relevant_places": {
"schools": [...],
"transit": [...],
"grocery": [...],
"parks": [...],
"restaurants": [...]
},
"location": {"lat": 40.7589, "lon": -73.9851},
"search_radius": 1000,
"total_places_found": 63,
"context_insights": "This area offers strong walkability with multiple grocery options within 500m..."
Examples
Evaluate a suburban address
./scripts/real-estate.sh '{"address": "123 Oak Street, Palo Alto, CA", "radius": 1500}'
Evaluate an urban apartment
./scripts/real-estate.sh '{"location": {"lat": 40.7484, "lon": -73.9857}, "radius": 800}'
Evaluate a neighborhood by coordinates
./scripts/real-estate.sh '{"location": {"lat": 37.7749, "lon": -122.4194}, "radius": 2000}'
Best Practices
- Use
address for street addresses; the script will geocode them automatically
- Use
location with lat/lon when you already have coordinates
- Start with a 1000m radius for suburban areas, 500m for dense urban areas
- Combine with the
relationship skill to calculate commute distances to workplaces
- Combine with the
route skill to estimate travel times to key destinations
- Use the
school-finder skill for more detailed school searches