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sg-property-scraperSG 财产刮刀

Agent Skill

sg-property-scraper 用于处理浏览器自动化、网页检查和页面信息提取,适合在 OpenClaw 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

22,250

周安装

946

GitHub Stars

公开资料未说明

下载量

7,795
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:sg-property-scraper(SG 财产刮刀)
来源仓库:https://github.com/5kbpers/sg-property-scraper
安装命令:
openclaw skills install sg-property-scraper
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install sg-property-scraper

简介

sg-property-scraper 用于灵活过滤新加坡房产租赁与销售列表。

  • 适合在 OpenClaw 中搜索出租或出售房源、检查市场信息时使用。
  • 通过安装命令 openclaw skills install sg-property-scraper 集成到项目。
  • 使用前需确认是否涉及第三方平台访问及数据使用合规性。
  • 适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

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

Singapore Property Scraper

Scrapes Singapore property listings via HTTP requests. Returns structured JSON.

Script Location

scripts/scrape.py

Relative to this SKILL directory. Run with:

python3 <SKILL_DIR>/scripts/scrape.py [OPTIONS]

Dependencies

  • Python 3.8+
  • pip install curl_cffi beautifulsoup4 lxml
  • Optional: GOOGLE_MAPS_API_KEY env var for commute time calculation (Google Routes API)

Quick Start

# 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

Filter Parameters

FlagURL ParamTypeDescription
--listing-typelistingTypestringrent or sale
--property-type-grouppropertyTypeGroupstring (repeatable)N=Condo, L=Landed, H=HDB
--entire-unit-or-roomentireUnitOrRoomstringent for entire unit only; omit for all
--room-typeroomTypestring (repeatable)master, common, shared
--bedroomsbedroomsint-1=room, 0=studio, 1-5
--bathroomsbathroomsintNumber of bathrooms
--min-priceminPriceintMinimum price (SGD)
--max-pricemaxPriceintMaximum price (SGD)
--min-sizeminSizeintMinimum size (sqft)
--max-sizemaxSizeintMaximum size (sqft)
--min-top-yearminTopYearintMinimum TOP year
--max-top-yearmaxTopYearintMaximum TOP year
--distance-to-mrtdistanceToMRTfloatMax distance to MRT in km (e.g. 0.5, 0.75)
--availabilityavailabilityintAvailability filter
--mrt-stationmrtStationsstring (repeatable)MRT station code, e.g. CC20
--mrt-rangemrtStationsstring (repeatable)MRT range, e.g. CC:20-24
--sortsortstringdate, price, psf, size
--orderorderstringasc, desc
--commute-tocommuteTostringDestination address for commute time (requires GOOGLE_MAPS_API_KEY)

Bedroom/Room Logic

  • --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)
  • Omit --entire-unit-or-room to show both entire units and rooms

MRT Station Syntax

  • Individual station: --mrt-station CC20
  • Range (same line): --mrt-range CC:20-24 (expands to CC20, CC21, CC22, CC23, CC24)
  • Multiple lines: use multiple flags
  • In JSON: "mrtStations": ["CC20", "EW15"] or [["CC", [20, 24]]] (tuple format)

See references/params.md for the complete list of ~213 valid MRT station codes.

Execution Parameters

FlagDescription
--pages NNumber of pages to scrape (default: 1)
--dry-runBuild and print URL(s), skip scraping
--no-validateSkip parameter validation
--timeout NHTTP request timeout in seconds (default: 30)
--raw-param K=VExtra URL query param (repeatable)
`--output json\text\none`Output format (default: json when piped)
--verboseVerbose logging to stderr

JSON Input Mode

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

Output Format

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"
  }
]

Exit Codes

  • 0: Success, results found
  • 1: Error (bad parameters, scraping failure)
  • 2: Success but zero listings found

Agent Usage Notes

When calling this script from an AI agent:

  1. Use --output json for structured output (default when piped)
  2. Use --json flag for easier parameter passing than individual CLI flags
  3. Use --dry-run to preview the search URL before scraping
  4. Use --pages N if the user wants more results (each page has ~20 listings)
  5. Use --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.
  6. commute_driving and commute_transit fields are empty strings "" when API key is missing or calculation fails

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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按下载量换算6,623

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