CCARF Practice Question

Paper 5 · Question 16

D4 Prompt Engineering & Structured Output · Paper 5

[Scenario: Claude Code for Continuous Integration] Your automated reviews find real issues, but developers report the feedback is not actionable. Findings include phrases like “complex ticket routing logic” or “potential null pointer” without specifying what exactly to change. When you add detailed instructions like “always include concrete fix suggestions,” the model still produces inconsistent output—sometimes detailed, sometimes vague. Which prompting technique most reliably produces consistently actionable feedback? Which prompting technique is most reliable?

• A.Further refine instructions with more explicit requirements for each part of the feedback format (location, issue, severity, proposed fix).
• B.Expand the context window to include more surrounding codebase so the model has enough information to propose concrete fixes.
• C.Implement a two-pass approach where one prompt identifies issues and a second generates fixes, allowing specialization.
• D.Add 3–4 few-shot examples showing the exact required format: identified issue, location in code, concrete fix suggestion.

Show answer & explanations

Correct answer: D

A: The team already tightened the instructions, and the format still drifted. More prose repeats the technique that is not holding.

B: A larger context does not teach the output shape. The findings are vague because the template is not anchored.

C: A second pass can specialise the work, but neither pass will hold the format if it is never shown.

D: Few-shot examples are the most effective technique for achieving consistent output format when instructions alone produce variable results. Providing 3–4 examples that show the exact desired structure (issue, location, concrete fix) gives the model a concrete pattern to follow, which is more reliable than abstract instructions.

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