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DeepSeek Prompt Generator for Real Estate
Describe your real estate task in plain words and get an engineered DeepSeek prompt — one direct user message with no separate system prompt. Switch to any of 32 AIs to see the same request rewritten for that model. Free, private and instant.
DeepSeek prompt generator
You are a senior real-estate marketing copywriter and agent coach who understands buyer psychology, local-market positioning and fair-housing rules. Write a listing description for a renovated 3-bedroom townhouse with a private garden. Background: - Target buyers: young families relocating for work - Lead with the single strongest feature, then lifestyle benefits, then practical facts (beds, baths, size, parking). - Facts to include: 2 bathrooms, 1,450 sq ft, 5-minute walk to a top-rated school, new kitchen, EV charger Requirements: - Follow fair-housing rules: describe the property, never the kind of person who should live there. - Use concrete, sensory details instead of clichés like 'must see' or 'nestled'. - No exaggerated or unverifiable claims. - Tone: professional. Output: A headline (max 10 words), a 150–200 word description in short paragraphs and 5 bullet-point highlights. If anything essential is missing, ask me up to 3 short clarifying questions before you start.
- ›DeepSeek's reasoning mode works best with everything in a single user message — no separate system prompt.
- ›Skip few-shot examples for reasoning tasks; describe the output you want instead.
- ›For maths or logic, ask it to reason step by step and give the final answer at the end.
How the DeepSeek prompt is structured
DeepSeek's guidance for its reasoning models is to put all instructions in one user message, without a separate system prompt or few-shot examples. The generator writes it that way.
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.
DeepSeek prompting tips
- DeepSeek's reasoning mode works best with everything in a single user message — no separate system prompt.
- Skip few-shot examples for reasoning tasks; describe the output you want instead.
- For maths or logic, ask it to reason step by step and give the final answer at the end.
Real Estate prompt types
Choose a prompt type for real estate; each comes with an expert role, context rules and an output format:
- Property listing description — for example “a listing description for a renovated 3-bedroom townhouse with a private garden”.
- Seller lead follow-up email — for example “a follow-up email to a homeowner who requested a valuation last month”.
- Social media content plan — for example “a 2-week Instagram and Facebook content plan for a local real-estate agent”.
Example output for DeepSeek:
You are a senior real-estate marketing copywriter and agent coach who understands buyer psychology, local-market positioning and fair-housing rules. Write a listing description for a renovated 3-bedroom townhouse with a private garden. Background: - Target buyers: young families relocating for work - Lead with the single strongest feature, then lifestyle benefits, then practical facts (beds, baths, size, parking). - Facts to include: 2 bathrooms, 1,450 sq ft, 5-minute walk to a top-rated school, new kitchen, EV charger Requirements: - Follow fair-housing rules: describe the property, never the kind of person who should live there. - Use concrete, sensory details instead of clichés like 'must see' or 'nestled'. - No exaggerated or unverifiable claims. - Tone: professional. Output: A headline (max 10 words), a 150–200 word description in short paragraphs and 5 bullet-point highlights. If anything essential is missing, ask me up to 3 short clarifying questions before you start.
AI chat tools compared
| AI | Made by | Prompt style |
|---|---|---|
| DeepSeek | DeepSeek | one direct user message with no separate system prompt |
| ChatGPT | OpenAI | Markdown sections (Role, Task, Context, Constraints, Output format) |
| Claude | Anthropic | XML tags (<role>, <context>, <task>, <constraints>, <output_format>) |
| Gemini | Google's Persona · Task · Context · Format framework | |
| Microsoft Copilot | Microsoft | Microsoft's Goal · Context · Source · Expectations framework |
| Perplexity | Perplexity AI | a research brief with scope, sources and citations |
| Grok | xAI | Markdown sections (Role, Task, Context, Constraints, Output format) |
| Meta AI | Meta | Markdown sections (Role, Task, Context, Constraints, Output format) |
| Mistral Le Chat | Mistral AI | Markdown sections (Role, Task, Context, Constraints, Output format) |
| Qwen | Alibaba Cloud | Markdown sections (Role, Task, Context, Constraints, Output format) |