What is the Amplihack testing pyramid?

It is a strategic framework that recommends a test distribution of 60% unit tests, 30% integration tests, and 10% end-to-end (E2E) tests to maximize reliability while minimizing brittleness.

Does it provide actual code templates?

Yes, it generates functional test code templates for unit, integration, and E2E tests that can be immediately adapted to your testing framework.

Which programming languages are supported?

The Test Gap Analyzer currently scans and analyzes codebases written in Python, JavaScript, TypeScript, and Go.

Can it integrate with existing coverage tools?

Yes, it can parse existing reports like coverage.py (.coverage) for Python projects and coverage.json for other environments to refine its analysis.

How does it help with edge case testing?

The skill analyzes function logic to suggest specific tests for null/None inputs, boundary values, resource limits, and error paths that are often overlooked by manual testing.

Test Gap Analyzer

Name: Test Gap Analyzer
Author: rysweet

byrysweet

•

Seguridad y Pruebas

Identifies untested code paths and generates specific test suggestions to improve software reliability and coverage.

Acerca de

The Test Gap Analyzer is a specialized Claude Code skill designed to systematically scan codebases for missing tests and low-coverage areas. By following the Amplihack testing pyramid methodology—60% unit, 30% integration, and 10% E2E—it identifies high-risk functions, suggests missing edge cases, and provides ready-to-use test templates for Python, JavaScript, TypeScript, and Go. This skill is essential for teams looking to prioritize testing efforts based on risk and effort, ensuring that critical logic and error paths are never left unverified during the development lifecycle.

Características Principales

Risk-based prioritization of untested functions and critical code paths
Specific edge case discovery for boundary values and error handling
Actionable effort estimation for reaching coverage thresholds
Ready-to-use test template generation for unit, integration, and E2E tests
17 GitHub stars
Automated coverage gap identification across multiple programming languages

Casos de Uso

Reviewing Pull Requests to ensure new code meets testing requirements
Systematically improving coverage in legacy codebases using risk analysis
Planning comprehensive test strategies for new modules and features

Acerca de

Características Principales

Risk-based prioritization of untested functions and critical code paths
Specific edge case discovery for boundary values and error handling
Actionable effort estimation for reaching coverage thresholds
Ready-to-use test template generation for unit, integration, and E2E tests
17 GitHub stars
Automated coverage gap identification across multiple programming languages

Casos de Uso

Reviewing Pull Requests to ensure new code meets testing requirements
Systematically improving coverage in legacy codebases using risk analysis
Planning comprehensive test strategies for new modules and features