Prompt Engineering Fundamentals
Last reviewed
Correct answer: A. Completeness is the measure, not length: a short prompt can omit something needed
Explanation
The principle — Prompt quality is a question of whether everything needed is present, and length is only a side effect of that.
Why the key is correct — Google's guidance is to include the instructions and information the model needs to solve the problem instead of assuming it already has them. A short prompt is fine when nothing needed was left out, and poor when something was — so completeness is the thing being measured.
Why the others are wrong — Padding does not buy accuracy, and Google lists redundancy as a fault. Under-specification produces guessing rather than creativity. And "brief" fails because it cannot be measured, not because it is misapplied.
Remember this — Ask what the model could not possibly know. Add that, and nothing else.
Sources — Google, Prompt design strategies.
Sources
“You can include instructions and information in a prompt that the model needs to solve a problem, instead of assuming that the model has all of the required information.”
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