debt-sentinel

You can prevent hardcoded secrets and SQL injection vulnerabilities by using automated code scanning to block critical violations before they are committed. This approach applies pattern matching during code review workflows to detect anti-patterns and alert developers to security risks immediately.

To calculate and track technical debt scores, the system logs less critical code quality issues like inline styles and magic numbers. It assigns a debt score to each detected anti-pattern, allowing teams to monitor technical debt accumulation over time without blocking the commit process.

Yes, you can add custom anti-patterns to your code quality rule set. The system provides a configurable rule set for violation detection, allowing users to define their own specific pattern matching rules alongside the default security and debt tracking checks.

To enforce architectural patterns and prevent technical debt automatically, integrate pattern matching scripts into your code editing and review workflows. This setup automatically blocks critical violations and logs debt scores for less severe issues during the development process.

Yes, you need Python to run automated vulnerability scanning and pattern enforcement. The system requires Python scripts to perform the pattern matching and execute the configurable rule set used for detecting anti-patterns, hardcoded secrets, and SQL injection vulnerabilities.