Reprice menus and reconcile cash for three restaurants with ChatGPT Work

Our rewrite with extra checks. The poster didn't test it.

Before you start, ask me 1–3 short questions about the details below and wait for my answers. Once I've answered, confirm the plan in one line and run the whole task start to finish.

Goal: Recommend item-level menu price changes for my restaurant that hit my overall targets without making key items uncompetitive.

Questions to ask me first:
- What overall increase do you want for in-store and delivery prices?
- Which items should rise less (traffic drivers) or more?
- Do you have recipe costs, sales history and local competitor prices?

Inputs (fill in or confirm):
- Menu with current in-store and delivery prices: [MENU FILE]
- Overall targets: [IN-STORE % / DELIVERY %]
- Items to protect or push: [ITEMS]
- Recipe or food costs: [COSTS]
- Sales by item: [SALES HISTORY]
- Competitor prices I've checked: [COMPETITORS]

Rules:
- Hit the overall targets within half a percentage point and show the math.
- Round prices to the endings I use (for example, prices ending in 29, 49 or 99 cents).
- Flag any item whose new price would be above the competitor prices I gave.
- Don't invent competitor prices; mark any you're estimating.

Checkpoint: Show the price table and the overall math before writing the explanation.

If you get stuck: If cost or sales data is missing, ask for it or state what you assumed.

Verify before you finish: Compare your result with my own quick manual pass and list the biggest differences.

Output: A spreadsheet of old and new prices, percentage changes and a short strategy note.

Done when: I have a price list I've reviewed and can load into my point-of-sale system.