risk-scoring

Automate code review routing by calculating a multidimensional risk score from task metadata signals like file changes and module criticality. A weighted scoring system then determines the appropriate review tier, directing code changes to Low, Medium, High, or Critical review levels automatically.

A multidimensional risk score for code changes evaluates multiple factors such as file modifications, module criticality, and security tags. By applying a weighted scoring system to these extracted risk signals, it quantifies the potential impact of a pull request on security and quality standards.

Escalate pull requests touching critical security modules by applying a weighted risk scoring system to the extracted task metadata. When the calculation identifies high-risk signals like data migration or security tags, it automatically routes the code changes to a critical review tier requiring security team sign-off.

You can use risk scoring to enforce security compliance in quality assurance pipelines. The skill calculates risk scores from task metadata and applies a weighted system to determine review tiers, ensuring that high-risk code changes meet security and quality standards without manual oversight.

Automated review escalation works without manual oversight by extracting risk signals from task metadata and applying a weighted scoring system. This process calculates a risk score to determine the review tier, routing code changes to the appropriate level and maintaining security standards automatically.

Calculating a risk score for a pull request requires metadata containing risk signals such as file changes, module criticality, and security tags. The skill extracts these signals from task metadata and applies a weighted scoring system to determine the appropriate review tier and routing.