A comprehensive AI agent skill for navigating real estate transactions with local-first privacy, affordability analysis, and offer strategy building.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install realestate
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 realestate 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 Real Estate Transaction & Affordability Assistant?
The realestate skill is a powerful addition to the library of Openclaw Skills designed to streamline the complex process of buying, selling, or renting properties. It functions as a local-first navigation system that empowers users to make informed decisions without compromising sensitive financial data to external listing services. By providing systematic property evaluation and evidence-based offer strategies, this skill acts as a technical companion for anyone navigating the high-stakes real estate market.
Integrating this skill allows your AI agent to handle the heavy lifting of calculating true monthly costs—including taxes, insurance, and maintenance—while maintaining a clear boundary that respects the role of licensed professionals. Whether you are house hunting or reviewing a lease agreement, this Openclaw Skills module ensures you have a structured, data-driven approach to every transaction milestone.
Real Estate Transaction & Affordability Assistant Use Cases
- Determining true home affordability based on income, debt, and downpayment.
- Conducting systematic property evaluations for potential home purchases.
- Developing evidence-based offer strategies using comparable market data.
- Generating detailed inspection checklists tailored to property age and type.
- Analyzing lease agreements to identify unusual clauses or potential red flags.
How Real Estate Transaction & Affordability Assistant Works
- The user provides financial or property-specific data via natural language prompts.
- The skill executes specialized Python scripts, such as calculate_affordability.py or evaluate_property.py, to process the input.
- All generated data, calculations, and evaluation notes are stored locally in the memory/realestate/ directory to maintain privacy.
- The agent synthesizes the script output to provide actionable insights, such as affordability limits or offer range recommendations.
- Users can track transaction milestones and compare multiple properties through persistent local JSON records.
Real Estate Transaction & Affordability Assistant Setup
To get started with this skill, ensure your AI environment is configured to run Python scripts and has the necessary directories created.
# Create the local data directory
mkdir -p memory/realestate/
# Initialize affordability data with your financial profile
python scripts/calculate_affordability.py --income 120000 --debts 800 --downpayment 60000
Real Estate Transaction & Affordability Assistant Data Schema & Taxonomy
The realestate skill organizes its data across several JSON files within the local environment to maintain privacy and structured tracking. This schema allows Openclaw Skills to maintain a long-term memory of your property search.
| File | Description |
|---|---|
| affordability.json | Stores income, debt ratios, and maximum purchase price calculations. |
| properties.json | Contains systematic evaluations and checklists for individual addresses. |
| offers.json | Tracks offer strategies, comparables, and contingency plans. |
| inspections.json | Logs findings and checklists from physical property inspections. |
| contracts.json | Stores review notes and flagged clauses from legal documents. |
| transactions.json | Monitors the lifecycle of the purchase or sale process. |
Real Estate Transaction & Affordability Assistant Advanced Features
- Local-first data architecture ensures sensitive financial information never leaves your machine.
- Evidence-based offer strategy building with comparable property analysis functionality.
- Multi-property comparison tools for data-driven decision making across multiple listings.
- Modular Python script architecture allows for easy extension into custom local market analysis.
- Automated lease review capabilities for highlighting potential legal risks in rental agreements.
SKILL.md
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