code-review-standards

Code review standards enforce a principal-engineer self-review on generated Python and SQL, checking correctness, complexity, and security before output. This prevents weak or unsafe code from being returned by applying rigorous quality checks during generation.

Checking generated code for security and testability requires a self-review process that evaluates edge cases, robustness, and secret-handling before output. This ensures unsafe code is corrected and meets universal naming and comment quality standards.

Yes, the code review skill works with Dockerfiles and YAML configurations, enforcing universal naming, comment, and secret-handling standards. It reviews these artifacts for correctness and robustness across any assistant session.

Automatically improving naming and comment quality in generated code requires applying self-review standards that enforce universal naming conventions and comment quality. Weak or hard-to-maintain code is corrected before being shown in the session.

A self-review process for refactoring code blocks is needed when code quality and safety matter, such as with API handlers or data pipelines. It ensures generated refactors pass rigorous checks for complexity, robustness, and testability.

Yes, you can use code review standards for data pipelines and API handlers to ensure code quality and safety. The self-review process checks correctness, edge cases, and security, correcting weak or unsafe code before output.