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 review calls the Claude API for each PR, using tool_use with a `report_findings` tool that returns a JSON array of finding objects (each with `file_path`, `line_number`, `severity`, `category`, and `description`). During testing on a large PR touching 30+ files, the response hits the `max_tokens` limit and the output is truncated mid-JSON, causing your pipeline's parser to fail.

What is the most effective way to handle this?

Accepted Answer

A. Split the review into multiple API calls that each analyze a subset of the changed files, then merge the resulting findings arrays.

Answer

B. Add retry logic that detects truncated JSON and re-sends the request with instructions to report only critical and high severity findings.

Answer

C. Switch from tool_use to prompting Claude to return findings as a markdown list.

Answer

D. Increase `max_tokens` to the model's maximum and instruct Claude to keep finding descriptions under 50 words each.

Question 130