Skill UI

A powerful skill for conducting structured, systematic code reviews for PRs and MRs. It goes beyond basic style checks, performing deep analysis such as blast radius tracing, comprehensive security scanning (SQLi, XSS, secrets), detecting breaking changes in APIs/DB schemas, and calculating test coverage delta. Ideal for reviewing large, complex, or security-sensitive code changes before merging.

This skill provides a structured workflow for porting existing Semgrep security rules to multiple target languages. It guides users through applicability analysis, test-first rule creation, and validation for each language variant, ensuring consistent and accurate security coverage across polyglot codebases.

A comprehensive guide to writing reliable and maintainable tests for Kotlin projects. This skill covers modern testing patterns using Kotest for various spec styles (FunSpec, BehaviorSpec), MockK for dependency mocking, and enforces TDD principles (RED/GREEN/REFACTOR). Learn how to implement unit tests, property-based testing, and ensure high code coverage with Kover.

This guide details how to implement coverage-guided fuzz testing using AFL++ within CI/CD pipelines. It covers building the fuzzing harness, utilizing advanced instrumentation (like AddressSanitizer), and configuring automated runs to discover memory corruption and input handling vulnerabilities in compiled applications. Ideal for strengthening DevSecOps practices and ensuring code reliability.

This guide provides a comprehensive workflow for Test-Driven Development (TDD) within Laravel applications. It covers best practices for writing unit, feature, and integration tests using modern tools like Pest and PHPUnit. Learn how to manage database states, mock external services, and achieve high code coverage efficiently.

Automates the static security analysis of Android APK/AAB files using the Mobile Security Framework (MobSF). This skill identifies critical vulnerabilities such as hardcoded secrets, insecure permissions, weak cryptography, and structural flaws (mapping to OWASP Mobile Top 10) without requiring application execution. It is essential for integrating security gates into CI/CD pipelines, performing pre-release quality assurance, and enhancing penetration testing coverage.

This advanced technique utilizes AFL++, a powerful fork of American Fuzzy Lop, to perform coverage-guided fuzzing on compiled binaries. It instruments targets and systematically mutates input data to explore deep, previously unreached code paths. Ideal for comprehensive security assessments, vulnerability discovery, and rigorous binary compatibility testing, it helps uncover crashes, memory corruption bugs, and security flaws.

A comprehensive guide to writing robust and maintainable tests in Rust. It covers various advanced testing patterns, including Unit, Integration, Async, and Property-Based testing. Learn how to apply the TDD (Test-Driven Development) cycle (RED-GREEN-REFACTOR) to enhance code reliability and ensure high code coverage.

This guide provides comprehensive testing patterns for C# and .NET applications. It covers best practices using xUnit, FluentAssertions, and advanced techniques like mocking (NSubstitute/Moq), parameterized testing, and full integration testing using Testcontainers and WebApplicationFactory. Ideal for improving test quality, coverage, and developing robust, maintainable codebases.

This guide provides comprehensive best practices for writing robust and effective unit tests using JUnit 5 in Java. It covers standard test structures (Arrange-Act-Assert), advanced data-driven testing using parameterized methods, best assertion practices (including AssertJ), and dependency isolation using mocking frameworks like Mockito. Ideal for developers aiming to improve code coverage and test reliability.

This tool automates the creation of robust Playwright end-to-end tests. Given a detailed user scenario, it executes a multi-step process using the Playwright MCP, generating high-quality, executable Playwright TypeScript code. It saves the test file and automatically runs and iterates the test until it passes, ensuring comprehensive functional coverage and reliable validation.

An advanced, AI-powered agent designed to generate comprehensive and workable unit tests for virtually any programming language (e.g., Python, C#, Java, Go, TypeScript). It operates via a sophisticated multi-agent pipeline (Research → Plan → Implement → Build → Test → Fix → Lint). This ensures generated tests are not only written following project conventions but also compile, pass all tests, and effectively improve code coverage.