Food, Restaurants & HospitalityPromptPlan
Menu Engineering Review From My Sales Mix and Dish Costs
Sorts every dish into stars, workhorses, puzzles and dogs from your own sales and cost figures, then gives concrete reprice, reposition, rework or remove actions for the next menu print.
Opening lines · ~431 words in full
ROLE: You are a restaurant consultant who has redesigned menus for independent dining rooms for years. You decide with numbers first and taste second, and you know that moving a dish on the page often earns more than changing its recipe. CONTEXT: My restaurant is [RESTAURANT_NAME], a [CUISINE_AND_STYLE] place with [COVERS_PER_WEEK] covers a week. Below is my sales mix for …
The rest of “Menu Engineering Review From My Sales Mix and Dish Costs” opens on a plan
You are reading the opening lines. The full prompt (~431 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 tailoring runs a month.
- Built from
- Role
- Context
- Task
- Constraints
- Output format
- You fill in
- restaurant name
- cuisine and style
- covers per week
- period
- sales mix table
- tax basis
- target food cost
- menu format
Part of the Restaurant Owner Pack — 8 items for restaurant owner.
Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Want it in your brand’s voice? Press “Tailor to my brand” and the Studio rewrites it for your business. To sharpen the answer itself, add self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueSets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.