A clarifying question obtains missing context before a task is completed. In prompt engineering, it narrows the intended audience, tone, output format, tools, and constraints so the resulting prompt fits its use case. section 9.3.1 section 9.3
Useful clarifying questions ask about:
- The target audience: beginner, intermediate, or advanced Python programmers. section 9.3.1
- The desired tone: formal and technical or casual and explanatory. section 9.3.1
- The output format: code snippets, bullet points, or a step-by-step guide. section 9.3.1
- The tools or libraries and any special constraints that affect the answer. section 9.3.1 section 9.3
Refining an API-request prompt
Given “Act as an expert Python programmer. Give me instructions on how to send an HTTP request to an API and display the response,” ask clarifying questions before rewriting it. The answers can determine whether the result should target beginners, use a particular tone, include code, follow steps, or rely on specified libraries. section 9.3.1
Use clarifying questions before optimization, not as decoration. Gather essential context, then refine the prompt for clarity, precision, and output quality; review the result because language models provide no guarantees. section 9.3.1 section 9.3
