You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The…

Question

You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.

Your automated reviewer uses a single prompt covering security issues, API design, and business logic correctness. Your evaluation suite shows strong recall for API design findings (82%) but poor recall for business logic edge cases in quiz scoring (34%). When you add few-shot examples of logic bugs to the prompt, logic recall improves to 41% but API design recall drops to 68%.

How should you address this trade-off to improve detection across both categories?

Accepted Answer

B. Split the review into separate focused prompts – one for security and API design, another for business logic – each with dedicated examples, then consolidate findings before posting.

Answer

A. Provide the full repository as context instead of just the changed files and surrounding code, giving the model deeper visibility into business logic patterns.

Answer

C. Upgrade to a more capable model tier, since its stronger reasoning will handle both concern types in a single prompt and eliminate the recall tradeoff.

Answer

D. Replace the few-shot examples with a detailed checklist of specific logic edge cases to verify, such as division-by-zero in score calculations and boundary conditions in grading thresholds.

Question 129