Camino AI 房地产技能：智能位置评估工具，分析学区交通便利设施

real-estate by barneyjm/camino-skills

74 周安装量

安装命令

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

🇨🇳中文介绍

安装

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

房地产侦察员

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。

设置

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。

🇺🇸English

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, ...}

广告位招租

在这里展示您的产品或服务

触达数万 AI 开发者，精准高效

联系我们

相关 Skills

FlyClaw：零登录航班聚合查询工具，Python实现多源航班信息与价格搜索

4,000,000 周安装

SoulTrace 人格评估 API - 基于五色心理模型的贝叶斯自适应测试

50,400 周安装

飞书OpenAPI Explorer：探索和调用未封装的飞书原生API接口

37,900 周安装

Lark Drive API 使用指南：飞书云文档、Wiki、表格 Token 处理与文件管理

37,500 周安装

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}'

通过坐标评估社区

./scripts/real-estate.sh '{"location": {"lat": 37.7749, "lon": -122.4194}, "radius": 2000}'

对于街道地址，使用 address；脚本会自动进行地理编码
当您已有坐标时，使用带有 lat/lon 的 location
郊区区域从 1000 米半径开始，密集城区从 500 米开始
与 relationship 技能结合使用，计算到工作地点的通勤距离
与 route 技能结合使用，估算到关键目的地的旅行时间
使用 school-finder 技能进行更详细的学校搜索

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..."
}

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}'

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

飞书视频会议CLI工具：lark-vc技能详解，高效搜索与管理会议记录与纪要

36,800 周安装

Camino AI 房地产技能：智能位置评估工具，分析学区交通便利设施

🇨🇳中文介绍

安装

房地产侦察员

设置

🇺🇸English

Installation

Real Estate Scout

Setup

相关 Skills

使用方法

通过 Shell 脚本

通过 curl

参数

响应格式

示例

评估郊区地址

评估城市公寓

通过坐标评估社区

最佳实践

Usage

Via Shell Script

Via curl

Parameters

Response Format

Examples

Evaluate a suburban address

Evaluate an urban apartment

Evaluate a neighborhood by coordinates

Best Practices

最新 Skills