A professional-grade real estate data tool for searching listings, agents, and property details via API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install realtor
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install realtor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is realtor?
The realtor skill is a high-performance Python tool designed for Openclaw Skills that provides a seamless bridge to Realtor.com data. It enables AI agents to perform complex real estate queries, ranging from live market searches for sales and rentals to detailed historical data on recently sold properties. This skill is part of a broader ecosystem that empowers developers to build automated research agents capable of understanding local market dynamics and identifying professional representation in specific geographic areas without any external library dependencies.
realtor Use Cases
- Automating property searches based on specific price and location criteria.
- Researching neighborhood market trends via recently sold property data.
- Finding and verifying real estate agents for professional networking or client referrals.
- Building custom rental property dashboards with real-time availability updates.
How realtor Works
- The user configures the API credentials and selects a specific command such as search-sale or search-rent.
- The skill processes input parameters like city, state code, postal code, or price filters.
- A secure request is dispatched to the Realtor API via RapidAPI using the provided API key.
- The skill parses the raw API response and returns structured JSON for the agent to consume programmatically.
- Optionally, the --human flag can be appended to generate a clean, formatted view of the data for manual review.
realtor Setup
To begin using this skill with Openclaw Skills, follow these steps:
- Obtain an API key from the Realtor API via RapidAPI.
- Ensure you have Python 3.10+ installed.
- Set your environment variable:
export REALTOR_API_KEY="your_api_key_here"
- Execute a search command to verify connectivity:
python3 scripts/realtor.py search-sale --city "San Francisco" --state_code CA --price_min 800000
realtor Data Schema & Taxonomy
The skill returns structured data optimized for AI consumption. Key data structures include:
| Data Object | Key Attributes |
|---|---|
| Property Listing | Address, price, bed/bath count, property_id, and listing status |
| Agent Profile | Professional name, NRDS ID, and contact metadata |
| Location Metadata | Auto-complete suggestions, city codes, and state identifiers |
| Transaction History | Recently sold prices, dates, and property specifications |
realtor Advanced Features
- Intelligent location auto-complete functionality to minimize input errors in autonomous agent workflows.
- Lightweight architecture utilizing only the Python standard library for maximum portability.
- Comprehensive agent lookup capabilities by name or NRDS ID for professional vetting.
- Support for advanced filtering including price ranges and specific property IDs for deep-dive analysis.
SKILL.md
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