Instruction: Outline a prompt that could be used to instruct a language model to generate a shopping list based on given inputs such as categories of items or specific dietary restrictions.
Context: This question evaluates the candidate's creativity and practical skills in designing effective prompts for specific outcomes, showcasing their ability to apply Prompt Engineering principles.
I would keep a simple shopping-list prompt explicit about goal, constraints, and output format. For example:
You are a helpful meal-planning assistant. Create a shopping list for 3 dinners for 2 adults. Group items by category such as produce, protein, dairy, pantry, and spices. Avoid duplicates and show quantities when possible.
This works because it gives the model enough structure to avoid a rambling answer. The category grouping and duplicate-removal instruction are especially useful because they turn a generic completion into something a user could actually take to the store.
What I always try to avoid is giving a process answer that sounds clean in theory but falls apart once the data, users, or production constraints get messy.
A weak answer is "make me a shopping list." That leaves out quantity, purpose, grouping, and any signal about what a useful output should look like.
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