Quality Metrics

About

The Quality Metrics skill empowers teams to move beyond vanity metrics by focusing on outcome-based measurements like bug escape rates, Mean Time to Detect (MTTD), and DORA metrics. It provides structured guidance for establishing real-time quality dashboards and configuring automated quality gates within CI/CD pipelines to ensure only stable code reaches production. By leveraging specialized agents, it analyzes historical trends and predicts future stability risks, ensuring that quality improvements are driven by meaningful data rather than activity-based snapshots.

Key Features

• Measurement of outcome-based KPIs including Bug Escape Rate and Test Effectiveness.
• Configuration of multi-stage Quality Gates for commits, PRs, and production releases.
• Automated tracking of DORA metrics: Deployment Frequency, Lead Time, MTTR, and Change Failure Rate.
• 111 GitHub stars
• Agent-assisted trend analysis to identify stability risks over 30, 60, or 90-day periods.
• Standardized dashboard design patterns for visualizing delivery and process quality.

Use Cases

• Defining automated blocking thresholds for CI/CD pipelines to prevent critical regressions.
• Establishing data-driven quality dashboards to track team performance and delivery stability.
• Evaluating testing effectiveness and justifying investments in quality engineering initiatives.