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Cursor Prompt Generator for Real Estate
Describe your real estate task in plain words and get an engineered Cursor prompt — an engineering ticket: goal, context, requirements, constraints and acceptance criteria. Switch to any of 32 AIs to see the same request rewritten for that model. Free, private and instant.
Cursor prompt generator
Cursor · coding
You are a senior full-stack engineer who writes clean, secure, tested, production-ready code. ## Goal Build a property listings website for a small real-estate agency. ## Context - Users: home buyers browsing on their phones - Stack and constraints: about 40 active listings; add a mortgage estimate on the detail page - Default stack if not specified: React + Tailwind CSS with mock listings in a JSON file ## Requirements 1. Property cards with photo, price, beds, baths and area 2. Filters for price range, bedrooms, property type and location 3. Property detail page with gallery, map placeholder and enquiry form 4. Saved favourites ## Constraints - Clean and trustworthy, generous whitespace, mobile-first. - Don't change unrelated code or public interfaces without asking. - Handle errors and edge cases; never hard-code secrets. - Add or update tests for the new behaviour. ## Acceptance criteria - Every requirement above works end to end. - Tests pass and the linter is clean. - Finish with a short summary of the changes and any trade-offs. If anything essential is missing, ask me up to 3 short clarifying questions before you start.
1,151 chars · ~288 tokens
Open Cursor
- ›@-mention the files and folders the change touches so Cursor loads the right context.
- ›Save recurring constraints as Project Rules so you don't repeat them.
- ›Ask the agent to write a plan first, then implement it step by step.
How the Cursor prompt is structured
Cursor works best with a ticket-style prompt: a clear goal, the context it can't see, numbered requirements, constraints and acceptance criteria it can check its own work against.
Every prompt is built from the same modular parts — role, task, context (your audience and details) and output format — then rendered in the style each AI follows best. Change the AI in the drop-down and the same request is rewritten instantly.
Cursor prompting tips
- @-mention the files and folders the change touches so Cursor loads the right context.
- Save recurring constraints as Project Rules so you don't repeat them.
- Ask the agent to write a plan first, then implement it step by step.
Real Estate prompt types
Choose a prompt type for real estate; each comes with an expert role, context rules and an output format:
- Property listings website — for example “a property listings website for a small real-estate agency”.
Example output for Cursor:
You are a senior full-stack engineer who writes clean, secure, tested, production-ready code. ## Goal Build a property listings website for a small real-estate agency. ## Context - Users: home buyers browsing on their phones - Stack and constraints: about 40 active listings; add a mortgage estimate on the detail page - Default stack if not specified: React + Tailwind CSS with mock listings in a JSON file ## Requirements 1. Property cards with photo, price, beds, baths and area 2. Filters for price range, bedrooms, property type and location 3. Property detail page with gallery, map placeholder and enquiry form 4. Saved favourites ## Constraints - Clean and trustworthy, generous whitespace, mobile-first. - Don't change unrelated code or public interfaces without asking. - Handle errors and edge cases; never hard-code secrets. - Add or update tests for the new behaviour. ## Acceptance criteria - Every requirement above works end to end. - Tests pass and the linter is clean. - Finish with a short summary of the changes and any trade-offs. If anything essential is missing, ask me up to 3 short clarifying questions before you start.
AI coding tools compared
| AI | Made by | Prompt style |
|---|---|---|
| Cursor | Anysphere | an engineering ticket: goal, context, requirements, constraints and acceptance criteria |
| GitHub Copilot | GitHub | an engineering ticket: goal, context, requirements, constraints and acceptance criteria |
| Lovable | Lovable | a product spec: features, screens, design and tech stack |
| Bolt.new | StackBlitz | a product spec: features, screens, design and tech stack |
| v0 | Vercel | a product spec: features, screens, design and tech stack |
| Replit Agent | Replit | a product spec: features, screens, design and tech stack |
Frequently asked questions
What is a Cursor prompt generator?
It turns a plain-language request into a structured prompt — role, task, context and output format — written the way Cursor follows best, so you get better answers on the first try.
Does this tool send my text to Cursor?
No. The prompt is assembled in your browser from templates. Nothing you type is sent to any server or AI until you paste it yourself.
Why does the prompt change when I switch AI?
Models are trained on different conventions: Claude responds well to XML tags, Gemini to Persona/Task/Context/Format, Midjourney to descriptors and --parameters, Suno to style tags and a lyric sheet. The generator rewrites the same request for each.
What if I leave a field empty?
The example shown in grey is used instead, so the prompt is always complete. Replace it with your own details for the best results.
Can I use these prompts for other real estate tasks?
Yes. Pick the closest prompt type and describe your own task — the real estate expertise in the role and context still applies.
Is the prompt generator free?
Yes — free, unlimited and no account needed.