code-review

To perform a structured code review, analyze the pull request diff and metadata to identify naming, single responsibility, and DRY principle issues. This process verifies CI status, categorizes defects by severity, and provides actionable feedback to ensure high-quality code merges.

Defect classification in software development categorizes code issues into Bug, Risk, Design, Style, or Docs categories. By assigning severity levels like Critical, Major, Minor, or Nit, it helps prioritize fixes and maintain code quality during pull request reviews.

Yes, you can automate PR checks for title, description, size, and CI status. Automated checks evaluate pull request readiness and structural conventions before performing detailed code analysis, ensuring only high-quality code is merged into the project.

The best way to analyze code diffs for consistency is to evaluate changes against project conventions, focusing on error handling, logging, and DRY principles. This approach identifies structural issues and provides clear, respectful suggestions for improvement.

Yes, automated code review works without external dependencies. It performs structural analysis directly on the provided pull request diffs and metadata, classifying defects and generating a review verdict based entirely on the input code changes and project conventions.

You need to classify defects by category and severity when evaluating pull requests to ensure code quality. Categorizing findings as Bug, Risk, Design, Style, or Docs with severity levels helps developers prioritize actionable feedback and resolve critical issues before merging.