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Gemini Prompt Generator for Restaurants & Food
Describe your restaurants & food task in plain words and get an engineered Gemini prompt — Google's Persona · Task · Context · Format framework. Switch to any of 32 AIs to see the same request rewritten for that model. Free, private and instant.
Gemini prompt generator
Persona: You are a hospitality marketing specialist and food writer who makes dishes sound irresistible and keeps restaurants' tables full. Task: Write menu descriptions for 8 dishes at a modern Indian bistro. Context: - Guests: young professionals and food lovers in London - Describe taste, texture and origin in 15–30 words per dish. - Details: signatures: butter chicken, paneer tikka, lamb biryani, mango lassi; 2 vegan options Constraints: - Avoid clichés such as 'mouth-watering' and 'delicious'. - Mark dietary labels (V, VG, GF) where given. - Tone: professional. Format: Dish name — description — dietary labels, grouped by menu section. If anything essential is missing, ask me up to 3 short clarifying questions before you start.
- ›Google's own guidance: give Gemini a Persona, a Task, Context and a Format.
- ›Attach files or Google Docs as extra context instead of pasting long text.
- ›Ask for a table when comparing options — you can export it to Google Sheets.
How the Gemini prompt is structured
Google's Gemini prompting guide organises prompts around four parts — Persona, Task, Context and Format. The generator fills each one from your plain-text answers.
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.
Gemini prompting tips
- Google's own guidance: give Gemini a Persona, a Task, Context and a Format.
- Attach files or Google Docs as extra context instead of pasting long text.
- Ask for a table when comparing options — you can export it to Google Sheets.
Restaurants & Food prompt types
Choose a prompt type for restaurants & food; each comes with an expert role, context rules and an output format:
- Menu descriptions — for example “menu descriptions for 8 dishes at a modern Indian bistro”.
- Reply to reviews — for example “replies to a 2-star Google review about slow service”.
- Promotion & social posts — for example “posts announcing a weekday lunch special”.
Example output for Gemini:
Persona: You are a hospitality marketing specialist and food writer who makes dishes sound irresistible and keeps restaurants' tables full. Task: Write menu descriptions for 8 dishes at a modern Indian bistro. Context: - Guests: young professionals and food lovers in London - Describe taste, texture and origin in 15–30 words per dish. - Details: signatures: butter chicken, paneer tikka, lamb biryani, mango lassi; 2 vegan options Constraints: - Avoid clichés such as 'mouth-watering' and 'delicious'. - Mark dietary labels (V, VG, GF) where given. - Tone: professional. Format: Dish name — description — dietary labels, grouped by menu section. 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 |
|---|---|---|
| Gemini | Google's Persona · Task · Context · Format framework | |
| ChatGPT | OpenAI | Markdown sections (Role, Task, Context, Constraints, Output format) |
| Claude | Anthropic | XML tags (<role>, <context>, <task>, <constraints>, <output_format>) |
| 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) |
| DeepSeek | DeepSeek | one direct user message with no separate system prompt |
| 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) |