Which file formats are supported for the test reports?

The skill supports HTML for browser viewing, PDF for formal documentation, and JSON for programmatic data processing and integration.

How does this skill help with failure analysis?

The skill automatically identifies failing tests and provides structured summaries, helping developers quickly pinpoint the root cause of issues.

Can it track test performance over time?

Yes, it performs trend analysis by comparing current results with historical data to identify performance improvements or regressions.

Does it support multiple testing frameworks?

Yes, it is designed to aggregate results from various test frameworks used within your project to provide a unified overview of your testing state.

Automated Test Report Generator

Name: Automated Test Report Generator
Author: BbgnsurfTech

byBbgnsurfTech

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Seguridad y Pruebas

Generates comprehensive test reports with coverage metrics, trend analysis, and stakeholder-ready exports in HTML, PDF, or JSON formats.

Acerca de

This skill empowers Claude to transform raw test data from various frameworks into actionable insights by calculating key performance indicators such as code coverage, pass rates, and execution duration. It simplifies the reporting process by aggregating disparate results and performing historical trend analysis to identify regressions or improvements over time, making it an essential tool for developers and QA engineers to maintain high code quality and communicate testing progress clearly to stakeholders.

Características Principales

Automated code coverage and pass rate calculation
In-depth failure analysis and reporting
Multi-format export options (HTML, PDF, JSON)
Historical trend analysis and regression tracking
Multi-framework test result aggregation
3 GitHub stars

Casos de Uso

Generating stakeholder-ready reports after CI/CD pipeline execution
Comparing current test performance against historical benchmarks
Analyzing code coverage to identify untested modules

Acerca de

Características Principales

Automated code coverage and pass rate calculation
In-depth failure analysis and reporting
Multi-format export options (HTML, PDF, JSON)
Historical trend analysis and regression tracking
Multi-framework test result aggregation
3 GitHub stars

Casos de Uso

Generating stakeholder-ready reports after CI/CD pipeline execution
Comparing current test performance against historical benchmarks
Analyzing code coverage to identify untested modules