Search Singapore property rental and sale listings with flexible filters. Use when asked to search Singapore properties, find rental or sale listings, check...
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install sg-property-scraper或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install sg-property-scraper⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/sg-property-scraper/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: sg-property-scraper description: Search Singapore property rental and sale listings with flexible filters. Use when asked to search Singapore properties, find rental or sale listings, check property prices near MRT stations, or compare commute times. Supports filtering by listing type (rent/sale), property type (HDB/Condo/Landed), bedrooms, bathrooms, price range, size, TOP year, MRT station codes, distance to MRT, room type, availability, and commute time to a destination. Outputs JSON to stdout. metadata: {"openclaw":{"requires":{"bins":["python3"]},"primaryEnv":"GOOGLE_MAPS_API_KEY"}} ---
Scrapes Singapore property listings via HTTP requests. Returns structured JSON.
scripts/scrape.py
Relative to this SKILL directory. Run with:
python3 <SKILL_DIR>/scripts/scrape.py [OPTIONS]
pip install curl_cffi beautifulsoup4 lxmlGOOGLE_MAPS_API_KEY env var for commute time calculation (Google Routes API)# Search 2BR condos for rent under SGD 4000 near Circle Line
python3 scripts/scrape.py \
--listing-type rent --bedrooms 2 --max-price 4000 \
--property-type-group N --mrt-range CC:20-24 \
--output json
# JSON input mode (easier for AI tools)
python3 scripts/scrape.py --json '{
"listingType": "rent",
"bedrooms": 2,
"maxPrice": 4000,
"propertyTypeGroup": ["N"],
"mrtStations": ["CC20","CC21","CC22","CC23","CC24"]
}'
# Dry run: print URL only without scraping
python3 scripts/scrape.py --dry-run --listing-type rent --bedrooms 3
| Flag | URL Param | Type | Description | |------|-----------|------|-------------| | --listing-type | listingType | string | rent or sale | | --property-type-group | propertyTypeGroup | string (repeatable) | N=Condo, L=Landed, H=HDB | | --entire-unit-or-room | entireUnitOrRoom | string | ent for entire unit only; omit for all | | --room-type | roomType | string (repeatable) | master, common, shared | | --bedrooms | bedrooms | int | -1=room, 0=studio, 1-5 | | --bathrooms | bathrooms | int | Number of bathrooms | | --min-price | minPrice | int | Minimum price (SGD) | | --max-price | maxPrice | int | Maximum price (SGD) | | --min-size | minSize | int | Minimum size (sqft) | | --max-size | maxSize | int | Maximum size (sqft) | | --min-top-year | minTopYear | int | Minimum TOP year | | --max-top-year | maxTopYear | int | Maximum TOP year | | --distance-to-mrt | distanceToMRT | float | Max distance to MRT in km (e.g. 0.5, 0.75) | | --availability | availability | int | Availability filter | | --mrt-station | mrtStations | string (repeatable) | MRT station code, e.g. CC20 | | --mrt-range | mrtStations | string (repeatable) | MRT range, e.g. CC:20-24 | | --sort | sort | string | date, price, psf, size | | --order | order | string | asc, desc | | --commute-to | commuteTo | string | Destination address for commute time (requires GOOGLE_MAPS_API_KEY) |
--entire-unit-or-room ent --bedrooms 4 = 4-bedroom entire unit--entire-unit-or-room ent --bedrooms 0 = studio--bedrooms -1 --room-type master --room-type common = room rental (master or common room)--entire-unit-or-room to show both entire units and rooms--mrt-station CC20--mrt-range CC:20-24 (expands to CC20, CC21, CC22, CC23, CC24)"mrtStations": ["CC20", "EW15"] or [["CC", [20, 24]]] (tuple format)See references/params.md for the complete list of ~213 valid MRT station codes.
| Flag | Description | |------|-------------| | --pages N | Number of pages to scrape (default: 1) | | --dry-run | Build and print URL(s), skip scraping | | --no-validate | Skip parameter validation | | --timeout N | HTTP request timeout in seconds (default: 30) | | --raw-param K=V | Extra URL query param (repeatable) | | --output json\|text\|none | Output format (default: json when piped) | | --verbose | Verbose logging to stderr |
Pass filters as a JSON string with --json. Keys use camelCase matching the URL parameter names:
python3 scripts/scrape.py --json '{
"listingType": "rent",
"propertyTypeGroup": ["N"],
"bedrooms": 2,
"bathrooms": 2,
"maxPrice": 4000,
"mrtStations": ["EW16", "EW17", "EW18"],
"distanceToMRT": 0.75,
"minTopYear": 1990
}'
Or load from a file: --config filters.json
JSON array on stdout (empty [] if no results):
[
{
"id": "23744236",
"name": "Kingsford Waterbay",
"price": "S$ 3,900 /mo",
"psf": "S$ 4.53 psf",
"address": "68 Upper Serangoon View",
"bedrooms": "2",
"bathrooms": "2",
"area": "861 sqft",
"type": "Condominium",
"built": "Built: 2018",
"availability": "Ready to Move",
"mrt_distance": "14 min (1.15 km) from SE4 Kangkar LRT Station",
"list_date": "Listed on Feb 15, 2026 (2d ago)",
"agent": "May Chong",
"agency": "PROPNEX REALTY PTE. LTD.",
"headline": "Perfect work from home unit, river facing, unblocked high floor cozy",
"link": "https://www.propertyguru.com.sg/listing/for-rent-kingsford-waterbay-23744236",
"commute_driving": "25 mins",
"commute_transit": "45 mins"
}
]
0: Success, results found1: Error (bad parameters, scraping failure)2: Success but zero listings foundWhen calling this script from an AI agent:
--output json for structured output (default when piped)--json flag for easier parameter passing than individual CLI flags--dry-run to preview the search URL before scraping--pages N if the user wants more results (each page has ~20 listings)--commute-to with a destination address to calculate commute times (driving + transit) for each listing. Requires GOOGLE_MAPS_API_KEY env var. If the key is not set, commute fields are omitted silently.commute_driving and commute_transit fields are empty strings "" when API key is missing or calculation fails安装 sg-property-scraper 后,可以对 AI 说这些话来触发它
Help me get started with sg-property-scraper
Explains what sg-property-scraper does, walks through the setup, and runs a quick demo based on your current project
Use sg-property-scraper to search Singapore property rental and sale listings with flexible fi...
Invokes sg-property-scraper with the right parameters and returns the result directly in the conversation
What can I do with sg-property-scraper in my data & analytics workflow?
Lists the top use cases for sg-property-scraper, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/sg-property-scraper/ 目录(个人级,所有项目可用),或 .claude/skills/sg-property-scraper/(项目级)。重启 AI 客户端后,用 /sg-property-scraper 主动调用,或让 AI 根据上下文自动发现并使用。
sg-property-scraper 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
sg-property-scraper 可免费安装使用。请查阅仓库了解许可证信息。
Search Singapore property rental and sale listings with flexible filters. Use when asked to search Singapore properties, find rental or sale listings, check...
sg-property-scraper 属于「Data & Analytics」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my data & analytics tasks using sg-property-scraper
Identifies repetitive steps in your workflow and sets up sg-property-scraper to handle them automatically