npx skills add https://github.com/barneyjm/camino-skills --skill real-estate配套技能:这是 Camino AI 位置智能套件的一部分。安装所有可用技能(query、places、relationship、context、route、journey、real-estate、hotel-finder、ev-charger、school-finder、parking-finder、fitness-finder、safety-checker、travel-planner)以获得全面覆盖。
# 从仓库安装所有技能
npx skills add https://github.com/barneyjm/camino-skills
# 或安装特定技能
npx skills add https://github.com/barneyjm/camino-skills --skill real-estate
通过 clawhub 安装:
npx clawhub@latest install real-estate
# 或: pnpm dlx clawhub@latest install real-estate
# 或: bunx clawhub@latest install real-estate
为购房者和租房者评估任何地址或位置。结合位置上下文分析和有针对性的便利设施搜索,以发现附近的学校、交通、杂货店、公园、餐厅和步行便利性洞察。
即时试用(无需注册): 获取一个包含 25 次调用的临时 API 密钥:
curl -s -X POST -H "Content-Type: application/json" \
-d '{"email": "you@example.com"}' \
https://api.getcamino.ai/trial/start
返回:{"api_key": "camino-xxx...", "calls_remaining": 25, ...}
要获得每月 1,000 次免费调用,请在 https://app.getcamino.ai/skills/activate 注册。
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
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.
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, ...}
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将您的密钥添加到 Claude Code:
添加到您的 ~/.claude/settings.json:
{
"env": {
"CAMINO_API_KEY": "your-api-key-here"
}
}
重启 Claude Code。
# 评估一个地址
./scripts/real-estate.sh '{"address": "742 Evergreen Terrace, Springfield", "radius": 1000}'
# 使用坐标评估
./scripts/real-estate.sh '{"location": {"lat": 40.7589, "lon": -73.9851}, "radius": 1500}'
# 为密集城区使用更小的半径进行评估
./scripts/real-estate.sh '{"address": "350 Fifth Avenue, New York, NY", "radius": 500}'
# 步骤 1:对地址进行地理编码
curl -H "X-API-Key: $CAMINO_API_KEY" \
"https://api.getcamino.ai/query?query=742+Evergreen+Terrace+Springfield&limit=1"
# 步骤 2:获取以房地产为重点的上下文
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"
| 参数 | 类型 | 必需 | 默认值 | 描述 |
|---|---|---|---|---|
| address | string | 否* | - | 要评估的街道地址(自动进行地理编码) |
| location | object | 否* | - | 要评估的坐标(包含 lat/lon) |
| radius | int | 否 | 1000 | 围绕位置的搜索半径(单位:米) |
*必须提供 address 或 location 中的一项。
{
"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..."
}
./scripts/real-estate.sh '{"address": "123 Oak Street, Palo Alto, CA", "radius": 1500}'
./scripts/real-estate.sh '{"location": {"lat": 40.7484, "lon": -73.9857}, "radius": 800}'
./scripts/real-estate.sh '{"location": {"lat": 37.7749, "lon": -122.4194}, "radius": 2000}'
address;脚本会自动进行地理编码locationrelationship 技能结合使用,计算到工作地点的通勤距离route 技能结合使用,估算到关键目的地的旅行时间school-finder 技能进行更详细的学校搜索每周安装量
40
仓库
首次出现
2026年2月9日
安全审计
已安装于
codex35
opencode35
gemini-cli34
amp34
github-copilot34
kimi-cli34
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.
# 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}'
# 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"
| 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.
{
"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..."
}
./scripts/real-estate.sh '{"address": "123 Oak Street, Palo Alto, CA", "radius": 1500}'
./scripts/real-estate.sh '{"location": {"lat": 40.7484, "lon": -73.9857}, "radius": 800}'
./scripts/real-estate.sh '{"location": {"lat": 37.7749, "lon": -122.4194}, "radius": 2000}'
address for street addresses; the script will geocode them automaticallylocation with lat/lon when you already have coordinatesrelationship skill to calculate commute distances to workplacesroute skill to estimate travel times to key destinationsschool-finder skill for more detailed school searchesWeekly Installs
40
Repository
First Seen
Feb 9, 2026
Security Audits
Installed on
codex35
opencode35
gemini-cli34
amp34
github-copilot34
kimi-cli34
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36,800 周安装