pi-seo-health-monitor

Detecting code health regressions across multiple repositories involves analyzing Pi-SEO scan history to compare consecutive scan cycles. This process flags portfolio health drops, sustained degradation, and systemic cross-repo issues by reading stored JSON scan results per project.

Portfolio health trend scoring computes a weighted composite health score across monitored projects using each project's individual scan priority. It evaluates scan history data to establish performance baselines and identify sustained degradation trends across multiple monitoring cycles.

Identifying systemic cross-repo issues in a multi-project repository requires matching scan type and title combinations that appear across multiple projects within the same scan cycle. This detects repeat findings that indicate widespread portfolio-level problems rather than isolated incidents.

Yes, generating alert digests from JSON scan results involves computing weighted portfolio health and emitting both structured JSON summaries and Markdown formatted alerts. The Markdown digest provides an operator-friendly format highlighting critical regressions and systemic issues.

Portfolio health monitoring requires scan results stored as JSON files per project and scan type across consecutive dates for trend comparison. It needs the latest two cycles per scan type to detect deltas and additional history loaded for sustained trend detection.

Tracking engineering quality degradation over time is best achieved by analyzing historical scan data to compute weighted portfolio health scores and flag persistent underperformance. This approach prevents hidden degradation by turning multi-cycle scan history into actionable portfolio-level alerts.