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RealtyAPI Skills for AI Agents

Practical AI agent skills for real estate research, powered by RealtyAPI.

These skills teach your AI agent how to use the RealtyAPI REST API — and how to turn public property data into useful research: property briefs, listing shortlists, rental research, CMAs (comparative market analyses), investment deal screening, and agent shortlists.

One API key, 30+ property portals worldwide — Redfin, Realtor.com, Zillow, Trulia, Homes.com, Apartments.com (US), Rightmove, Zoopla (UK), Idealista, SeLoger, Funda (Europe), Property Finder (Middle East), Domain (Australia), Airbnb, Vrbo, and more.

Install

npx skills add realtyapi/realtyapi-skills

Works with Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Windsurf, VS Code, and other agents that support the Agent Skills spec.

Or download any skills/<name>/SKILL.md and upload it to your AI tool manually.

Setup

Set your RealtyAPI key as an environment variable:

export REALTYAPI_API_KEY=rt_...

Get a key at realtyapi.io. The full endpoint index is public at realtyapi.io/llms.txt, and every provider exposes a keyless OpenAPI spec at https://<provider>.realtyapi.io/openapi.json.

Available Skills

Skill Use it when you want to... Output
realtyapi-api Route a raw real estate data request to the right RealtyAPI endpoint API calls, endpoint discovery, credit/pagination guidance
property-research Get a complete profile of one property by address or listing URL Property brief: details, history, value, comps, neighborhood
listing-search Find for-sale or sold homes matching criteria in an area Ranked listings table with source links
rental-market-research Research long-term or short-term rentals and rent trends Rental options + rent summary
comparative-market-analysis Estimate what a property is worth from comps and market data CMA report with a value range and reasoning
investment-deal-finder Find and screen foreclosures, discounts, and rental-yield deals Ranked deal candidates with equity/yield math
agent-finder Find or evaluate real estate agents in an area or for a property Vetted agent shortlist with evidence

Example Prompts

Here's a Redfin link — pull the full details, value estimate, and comps, and tell me if it's priced fairly.
Find 3-bed houses under $600k in Austin, sorted by price per square foot.
Run a CMA on 166 W 22nd St Unit 1D, New York, NY 10011 and give me a value range.
What does a 2-bed long-term rental cost in central Lisbon, and is rent rising?
Find foreclosure and price-reduced deals under $250k in Cuyahoga County and rank by equity.
Who are the most active listing agents in Scottsdale for homes around $1M?

How the Skills Work Together

realtyapi-api  (data layer: auth, endpoint discovery via llms.txt + openapi.json)
        │
        ▼
real estate workflows
 ├─ property-research
 ├─ listing-search
 ├─ rental-market-research
 ├─ comparative-market-analysis
 ├─ investment-deal-finder
 └─ agent-finder

The workflow skills use realtyapi-api as the data layer for endpoint details. Each workflow produces a useful artifact, not just raw JSON.

Design Principles

  1. Workflow-first, API-second — users ask for an outcome (a brief, a CMA), not an endpoint.
  2. Discover, don't guess — find endpoints in llms.txt, then read the provider's openapi.json for exact params before calling. Never hardcode/guess paths.
  3. Public-data only — RealtyAPI returns public real estate data. Don't promise private/MLS-restricted fields.
  4. Match portal to market — route each country/region to the right portal; there's no single global search.
  5. Cited outputs — include the source listing URL for every property, agent, or comp.
  6. Credit-aware — most calls cost 1 request credit; warn before pricier endpoints and cap pagination loops.
  7. Estimates ≠ appraisals — present valuations as ranges with confidence, not guarantees.

Links

License

MIT — see LICENSE.

About

Real estate research skills for AI agents — property briefs, listing search, rentals, CMAs, investment deal screening, and agent finders, powered by RealtyAPI

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