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Found 38 Skills
Vitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.
Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.
Analyze code coverage and CRAP (Change Risk Anti-Patterns) scores to identify high-risk code. Use OpenCover format with ReportGenerator for Risk Hotspots showing cyclomatic complexity and untested code paths.
Apex test execution, coverage analysis, and test-fix loops with 120-point scoring. Use when the user needs to run Apex tests, check code coverage, fix failing tests, or work with *Test.cls / *_Test.cls files. TRIGGER when: user runs Apex tests, checks code coverage, fixes failing tests, or touches *Test.cls / *_Test.cls files. DO NOT TRIGGER when: writing Apex production code (use platform-apex-generate), Agentforce agent testing (use agentforce-test), or Jest/LWC tests (use experience-lwc-generate).
Creates test infrastructure with Vitest, xUnit, and pytest
Test Node.js applications with Jest including unit tests, integration tests, mocking, code coverage, and CI/CD integration
Use the open-source free `coverlet` toolchain for .NET code coverage. Use when a repo needs line and branch coverage, collector versus MSBuild driver selection, or CI-safe coverage commands.
JaCoCo code coverage configuration for Java/Gradle projects. Covers report generation, coverage thresholds, multi-module aggregation, and SonarQube integration. Use when setting up or troubleshooting code coverage.
JaCoCo Java code coverage tool USE WHEN: user mentions "JaCoCo", "Java coverage", "code coverage", asks about "coverage threshold", "jacoco-maven-plugin", "coverage report", "LINE coverage", "BRANCH coverage" DO NOT USE FOR: JavaScript/TypeScript coverage - use Vitest skill, SonarQube analysis - use `sonarqube` skill, test execution - use testing skills
Expert in Python testing with pytest and test-driven development
Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating the improvement with a clean coverage comparison. Also opens a PR proposing .meticulousignore entries for code that structurally never executes in-browser. Use when asked to "increase coverage", "find untested code", or "add .meticulousignore entries" for a project.
Coverage analysis measures code exercised during fuzzing. Use when assessing harness effectiveness or identifying fuzzing blockers.