Order catering for a meeting with dietary needs covered
Quantities, menu choices, allergen handling, and a clear catering order for a meeting or event, with nobody left out.
The prompt
Help me plan catering for a meeting or event.
Event: [type, date, start and end time]
Number of people: [CONFIRMED + EXPECTED]
Dietary requirements and allergies collected: [e.g. "3 vegetarian, 1 vegan, 1 celiac, 1 severe nut allergy, 2 halal"]
Meals and breaks needed: [arrival coffee, lunch, afternoon break, drinks]
Budget: [PER PERSON OR TOTAL]
Caterer or options: [who we use, or what's nearby]
Setting: [boardroom, standing reception, working lunch at desks]
Give me:
1. Quantities: per item, with the assumptions shown (e.g. portions per person, a buffer of 5-10% for expected attendees).
2. Menu suggestions that suit the setting (easy to eat while talking for a working lunch) and cover dietary needs within the main menu where possible, so people aren't singled out.
3. Allergen plan: separately labeled and packed meals for serious allergies, labeling of all dishes, and confirming the caterer's allergen procedures. For severe allergies, tell me to confirm directly with the caterer and the attendee - never assume a dish is safe.
4. Order email to the caterer: date, delivery time and location, access instructions, quantities, dietary meals with names on labels, equipment (plates, cutlery, napkins), setup and collection times, budget, and request for confirmation.
5. Day-of checklist: delivery check against the order, labels, sustainability (leftovers, waste), and invoice.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Projects & Operations prompts
What to fill in
- type, date, start and end time
- CONFIRMED + EXPECTED
- arrival coffee, lunch, afternoon break, drinks
- PER PERSON OR TOTAL
- who we use, or what's nearby
- boardroom, standing reception, working lunch at desks
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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