How does this skill help with quality gates?

It defines automated thresholds for test pass rates, security vulnerabilities, and performance that can block or warn during commits, PRs, or releases to ensure code standards are met.

Which AI agents are involved in these quality workflows?

The skill coordinates specialized agents including the qe-quality-analyzer for trends, the qe-test-executor for data collection, and the qe-quality-gate for enforcement decisions.

Can this skill integrate with dashboards like Grafana?

Yes, the skill includes implementation patterns for agents to generate configurations for visualization tools like Grafana based on delivery, quality, and stability metrics.

What are DORA metrics?

DORA metrics are four key indicators—Deployment Frequency, Lead Time for Changes, Change Failure Rate, and MTTR—used to measure the performance and stability of software development teams.

Why focus on Bug Escape Rate over Code Coverage?

Code coverage measures activity (lines touched), while Bug Escape Rate measures outcomes (how many bugs reach production), providing a more accurate picture of actual software quality.

Quality Metrics

Name: Quality Metrics
Author: DreamLab-AI

byDreamLab-AI

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Analíticas y Monitorización

Measures software quality through actionable DORA metrics and automated quality gates to drive continuous improvement.

Acerca de

The Quality Metrics skill empowers developers and quality engineers to move beyond vanity metrics and focus on outcomes that matter. It provides a structured framework for implementing DORA metrics (Deployment Frequency, Lead Time, Change Failure Rate, MTTR), establishing automated quality gates that block subpar code, and generating comprehensive dashboards for long-term trend analysis. By utilizing agentic workflows, it automates the collection and evaluation of data like bug escape rates and defect density, ensuring that software quality remains a data-driven priority throughout the SDLC.

Características Principales

Generates actionable quality dashboards using agent-assisted trend analysis
1 GitHub stars
Configures automated quality gates to enforce performance and reliability standards
Identifies and mitigates common measurement traps like coverage worship
Implements core DORA metrics for tracking delivery speed and stability
Calculates critical indicators like Bug Escape Rate and Test Effectiveness

Casos de Uso

Defining blocking thresholds for CI/CD pipelines to prevent regressions
Establishing a data-driven quality dashboard for a new software project
Evaluating the effectiveness of a testing strategy over a 90-day period

Acerca de

Características Principales

Generates actionable quality dashboards using agent-assisted trend analysis
1 GitHub stars
Configures automated quality gates to enforce performance and reliability standards
Identifies and mitigates common measurement traps like coverage worship
Implements core DORA metrics for tracking delivery speed and stability
Calculates critical indicators like Bug Escape Rate and Test Effectiveness

Casos de Uso

Defining blocking thresholds for CI/CD pipelines to prevent regressions
Establishing a data-driven quality dashboard for a new software project
Evaluating the effectiveness of a testing strategy over a 90-day period