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

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 pipeline reviews every pull request using a single API call with a static prompt containing the diff and the full text of each changed file. Unchanged files are not included. Developers report that reviews consistently miss cross-file bugs—for example, a pull request renames a function’s parameters, but the review does not identify callers in unchanged files that still use the old argument order.

Evaluation shows that cross-file bugs account for 35% of production incidents originating from reviewed pull requests.

What is the most effective change to the review design?

A.

Build a static dependency graph and include every file located within two dependency hops of a changed file.

B.

Add instructions asking the model to list external references and reason step by step about how each change could affect unseen callers.

C.

Redesign the review as a turn-limited agentic task that can read files and search the repository, following references to verify cross-file findings.

D.

Run separate review passes for each changed file with its direct dependants, and then aggregate and deduplicate the findings through a final consolidation pass.

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