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.

Install all skills from repo

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

Or install specific skills

npx skills add https://github.com/barneyjm/camino-skills --skill real-estate Via clawhub: npx clawhub@latest install real-estate

or: pnpm dlx clawhub@latest install real-estate

or: bunx 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

Evaluate an address

./scripts/real-estate.sh '{"address": "742 Evergreen Terrace, Springfield", "radius": 1000}'

Evaluate with coordinates

./scripts/real-estate.sh '{"location": {"lat": 40.7589, "lon": -73.9851}, "radius": 1500}'

Evaluate with smaller radius for dense urban area

./scripts/real-estate.sh '{"address": "350 Fifth Avenue, New York, NY", "radius": 500}' Via curl

Step 1: Geocode the address

curl -H "X-API-Key: $CAMINO_API_KEY " \ "https://api.getcamino.ai/query?query=742+Evergreen+Terrace+Springfield&limit=1"

Step 2: Get context with real estate focus

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