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Found 13 Skills
cargo-fuzz is the de facto fuzzing tool for Rust projects using Cargo. Use for fuzzing Rust code with libFuzzer backend.
OSS-Fuzz provides free continuous fuzzing for open source projects. Use when setting up continuous fuzzing infrastructure or enrolling projects.
Test-driven development workflow with test generation, coverage analysis, and multi-framework support
Comprehensive QA and testing skill for quality assurance, test automation, and testing strategies for ReactJS, NextJS, NodeJS applications. Includes test suite generation, coverage analysis, E2E testing setup, and quality metrics. Use when designing test strategies, writing test cases, implementing test automation, performing manual testing, or analyzing test coverage.
This skill should be used when the user asks to "generate tests", "write unit tests", "analyze test coverage", "scaffold E2E tests", "set up Playwright", "configure Jest", "implement testing patterns", or "improve test quality". Use for React/Next.js testing with Jest, React Testing Library, and Playwright.
Generate comprehensive, maintainable unit tests across languages with strong coverage and edge case focus.
Use when reviewing or scoring AI-generated unit tests/UT code, especially when coverage, assertion effectiveness, or test quality is in question and a numeric score, risk level, or must-fix checklist is needed
Testing expert with comprehensive knowledge of test structure, mocking strategies, async testing, coverage analysis, and cross-framework debugging. Use PROACTIVELY for test reliability, flaky test debugging, framework migration, and testing architecture decisions. Covers Jest, Vitest, Playwright, and Testing Library.
Comprehensive QA testing orchestrator. Use when user says 'test', 'qa', 'check site', 'find bugs', 'helpmetest', provides a URL to test, or wants complete testing coverage from discovery through bug reporting. Discovers ALL pages, enumerates ALL features, tests comprehensively, reports exact metrics.
Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
Use when validating golden dataset quality. Runs schema checks, duplicate detection, and coverage analysis to ensure dataset integrity for AI evaluation.
Generate a visual spec-to-code coverage map showing which code files are covered by which specifications. Creates ASCII diagrams, reverse indexes, and coverage statistics. Use after implementation or during cleanup to validate spec coverage.