Jump to related tools in the same category or review the original source on GitHub.

Transportation @james-southendsolutions Updated 7/15/2026 1,572 downloads 6 stars Security: Pass

๐Ÿ  Camino Real Estate OpenClaw Plugin & Skill | ClawHub

Looking to integrate Camino Real Estate into your AI workflows? This free OpenClaw plugin from ClawHub helps you automate transportation tasks instantly, without having to write custom tools from scratch.

What this skill does

Evaluate any address for home buyers and renters. Get nearby schools, transit, grocery stores, parks, restaurants, and walkability using Camino AI's location intelligence.

Install

ClawHub CLI
openclaw skills install @james-southendsolutions/camino-real-estate
Node.js (npx)
npx clawhub@latest install camino-real-estate

Full SKILL.md

Open original
Metadata table.
namedescription
camino-real-estateEvaluate any address for home buyers and renters. Get nearby schools, transit, grocery stores, parks, restaurants, and walkability using Camino AI's location intelligence.

SKILL.md content below is scrollable.

Installation

Companion Skills: This is part of the Camino AI location intelligence suite. Install all available skills (camino-query, camino-places, camino-relationship, camino-context, camino-route, camino-journey, camino-real-estate, camino-hotel-finder, camino-ev-charger, camino-school-finder, camino-parking-finder, camino-fitness-finder, camino-safety-checker, camino-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 camino-real-estate

Via clawhub:

npx clawhub@latest install camino-real-estate
# or: pnpm dlx clawhub@latest install camino-real-estate
# or: bunx clawhub@latest install camino-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

These skills shell out to curl and authenticate via the CAMINO_API_KEY environment variable. Sign up at https://app.getcamino.ai/skills/activate for 100 free calls/month and an API key.

Add your key to Claude Code:

Add to your ~/.claude/settings.json:

{
  "env": {
    "CAMINO_API_KEY": "your-api-key-here"
  }
}

Restart Claude Code.

Alternative โ€” pay-per-request via x402: Camino's paid endpoints also accept HTTP 402 payments in USDC on Base ($0.001/request) from any x402-capable client, with no signup or API key. These skills don't use this path; it's for agents and clients that speak x402 natively.

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 camino-relationship skill to calculate commute distances to workplaces
  • Combine with the camino-route skill to estimate travel times to key destinations
  • Use the camino-school-finder skill for more detailed school searches
ClawHub Registry URL: https://clawhub.ai/james-southendsolutions/skills/camino-real-estate

Related skills

If this matches your use case, these are close alternatives in the same category.