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.

The automated review consistently flags patterns your team uses intentionally – force-unwrapping optionals in test files, using large coordinator classes that follow your established architecture, and importing internally-maintained modules marked as deprecated in the public SDK. Developers are dismissing roughly 30% of all findings as project-specific false positives.

Which approach prevents the model from generating these findings in the first place by supplying the project's conventions as persistent context on every review?