test-reporting-analytics

Generate role-specific QE test dashboards and predictive analytics reports.

6|3|Updated Dec 3, 2025

Search Tags:#analytics #dashboards #executive-reporting #trend-analysis #predictive-analytics #test-reporting #QA-metrics

Ready to run

npx skills add https://github.com/pacphi/ampel --skill test-reporting-analytics-pacphi

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: test-reporting-analytics
Source: https://github.com/pacphi/ampel/tree/main/.claude/skills/test-reporting-analytics
Command: npx skills add https://github.com/pacphi/ampel --skill test-reporting-analytics-pacphi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables advanced test reporting, quality dashboards, predictive analytics, trend analysis, and executive reporting for QE metrics. It helps teams communicate quality status clearly, track trends over time, and make data-driven decisions.

Core Features & Use Cases

Dashboard Creation: generate concise, role-specific dashboards for developers, QA, and leadership.
Trend Analysis: visualize 30/60/90-day trends to identify improvements or regressions.
Predictive Insights: forecast likely failures and suggested actions to reduce risk.
Executive Reporting: translate technical metrics into business-impact summaries.
Use Case: A quarterly QE briefing highlighting escaped defects and MTTR to justify tooling investments.

Quick Start

Define your audience (devs, QE, executives), select 5-7 key metrics (pass rate, coverage, flaky tests, MTTR, deploy frequency, escaped defects, etc.), and generate a dashboard from the latest test run.

Frequently Asked Questions about test-reporting-analytics

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

FAQPage Schema

How do I create executive dashboards from test data?▼

Executive dashboards translate QE metrics into business-impact summaries tailored for leadership. This Skill automates dashboard generation for developers, QA, and executives by selecting 5-7 key metrics—pass rate, coverage, flaky tests, MTTR, deploy frequency, and escaped defects—then visualizing them with role-specific context to enable data-driven release decisions.

Can I track test quality trends over time?▼

Trend analysis visualizes 30/60/90-day patterns in QE metrics to identify improvements or regressions. This Skill forecasts likely failures and suggests actions to reduce risk, helping teams detect quality shifts early and justify tooling investments through measurable trend data.

What's the best way to automate test reporting for different audiences?▼

Audience-tailored reporting generates separate dashboards for developers, QE teams, and leadership using the same underlying metrics but formatted for each role's priorities. This Skill automates the transformation from raw test runs into concise, actionable summaries without manual report creation.

How do I detect anomalies in test results?▼

Anomaly detection identifies unexpected patterns—flaky tests, coverage drops, or failure spikes—within test data streams. This Skill integrates anomaly detection into predictive analytics to flag risks early and trigger alerts for QE teams before quality issues impact releases.

Does this work with existing CI/CD and QE agent workflows?▼

Yes. This Skill integrates with existing QE agent workflows and CI/CD pipelines, consuming test run data and producing dashboards, trend reports, and predictive insights without replacing current tools. It satisfies KPI definition, automated report generation, and anomaly detection requirements.

What metrics should I track for release readiness?▼

Key release-readiness metrics include pass rate, test coverage, flaky test count, mean-time-to-resolution (MTTR), deploy frequency, and escaped defects. This Skill helps define, measure, and communicate these KPIs across audiences to validate release quality and reduce deployment risk.