Real Estate Deal Finder
Every four hours, this agent scans six Facebook real estate groups for deals matching your criteria and texts you the details immediately.
What it does
You receive instant SMS alerts with real estate deal details whenever new posts matching your criteria appear in six monitored Facebook groups. This agent scans these groups every four hours, uses AI to extract key property information, and filters results against your custom requirements before notifying you immediately.
Step by step
- Configure an HTTP request node to poll the Facebook Graph API or a scraping service endpoint every four hours.
- Set up a Twilio SMS action with hardcoded account SID, auth token, and recipient phone number variables.
- Define the JSON schema for the output message including property address, price, and estimated ROI.
Where the LLM does the work
- Craft system prompts that instruct the model to ignore non-investment posts and focus on extracting specific deal metrics.
- Design few-shot examples within the prompt to demonstrate how to handle ambiguous or poorly formatted listing text.
- Implement logic to classify each extracted property against dynamic buy-box criteria such as max price or minimum equity.
Watch out for
Facebook frequently changes its API access policies so you must implement a fallback scraping method if the official endpoint breaks.
Twilio SMS costs can accumulate quickly with high volume, add a daily budget cap to prevent unexpected charges.
Tools that fit
HTTP Request API Scraping Facebook group posts via RapidAPI
OpenAI Chat Model LLM Extracting deal details and classifying offers
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Real Estate Deal Finder: Every four hours, this agent scans six Facebook real estate groups for deals matching your criteria and texts you the details immediately. ## Specification - What it does: You receive instant SMS alerts with real estate deal details whenever new posts matching your criteria appear in six monitored Facebook groups. This agent scans these groups every four hours, uses AI to extract key property information, and filters results against your custom requirements before notifying you immediately. - Trigger: On a schedule (Scheduled · every 4 hours) - Autonomy: Fully hands-off - Expected setup effort: under an hour - Tools/services involved: - HTTP Request: Scraping Facebook group posts via RapidAPI - OpenAI Chat Model: Extracting deal details and classifying offers - Twilio: Sending SMS alerts for qualifying deals ## Known pitfalls, handle each one explicitly in your implementation 1. Facebook frequently changes its API access policies so you must implement a fallback scraping method if the official endpoint breaks. 2. Twilio SMS costs can accumulate quickly with high volume, add a daily budget cap to prevent unexpected charges. ## Reference implementation https://n8n.io/workflows/15431 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/automated-real-estate-deal-finder/ via usecasesforagents.com
Frequently asked questions
Can I use a different LLM than OpenAI?
Yes. OpenAI is only the example LLM in this recipe. The same flow works with Anthropic, Cohere, DeepSeek and Google Gemini. Swap the LLM connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for founders and execs who need operations handled without hiring for it.