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qa-metrics

Analyze test execution metrics and enforce release readiness criteria.

2|1|Updated May 27, 2025
Search Tags:#qa#quality gates#regression testing#quality metrics#release validation#test analytics
One-click install
npx skills add https://github.com/VirtoCommerce/vc-mcp-testing-module --skill qa-metrics-virtocommerce
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qa-metrics
Source: https://github.com/VirtoCommerce/vc-mcp-testing-module/tree/main/skills/qa-metrics
Command: npx skills add https://github.com/VirtoCommerce/vc-mcp-testing-module --skill qa-metrics-virtocommerce

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps QA teams measure software quality consistently and make release decisions using objective metrics, thresholds, and evidence-based quality gates.

Core Features & Use Cases

  • Quality Metric Analysis: Defines and evaluates pass rates, defect density, coverage, DRE, flakiness, and other QA indicators from test results.
  • Release Gate Enforcement: Applies smoke, sprint, full release, and hotfix gate criteria to determine approval, conditional approval, or blocking decisions.
  • Use Case: A QA lead can use this Skill after a regression run to generate a quality report, analyze trends, and decide whether a deployment is ready.

Quick Start

Ask the qa-metrics skill to analyze the latest regression results and provide the release quality gate verdict.

Frequently Asked Questions about qa-metrics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce quality gates for release validation using test metrics?▼

Release validation enforces quality gates by evaluating test execution metrics against predefined threshold criteria to determine deployment approval, conditional approval, or blocking decisions. It applies deterministic pass rate, defect density, and flakiness calculations to regression results.

What QA metrics should I track for sprint reviews and regression reporting?▼

QA metrics for sprint reviews and regression reporting include pass rates, defect density, test coverage, defect removal efficiency (DRE), and test flakiness. Analyzing these indicators historically enables trend analysis and evidence-based release decisions.

How do I determine deployment readiness from regression test results?▼

Deployment readiness is determined by applying smoke, sprint, full release, or hotfix gate criteria to regression test results. The evaluation validates historical test data against quality thresholds to generate a clear deployment verdict.

Can I apply different quality gate thresholds for hotfixes versus full releases?▼

Different quality gate thresholds for hotfixes versus full releases are supported through distinct gate criteria configurations. Smoke, sprint, full release, and hotfix gates each apply specific metric threshold validation to determine the appropriate release decision.

How does trend analysis work with historical test data evaluation?▼

Trend analysis evaluates historical test data by tracking quality metrics like pass rates, defect density, and flakiness over time. Comparing deterministic metric calculations across regression runs reveals quality trajectories for sprint reviews and release planning.

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