Skill UI

Ruzzy is a coverage-guided Ruby fuzzer leveraging libFuzzer to exercise both pure Ruby code and native C extensions; follow the provided installer, harness patterns, and sanitizer-aware runs to validate Ruby apps or gems for memory safety issues.

Automates AWS SAM template building with best-practice guidance, production-ready code/config generation, validation, and coverage for compute, storage, networking, and serverless patterns when a user requests help with the SAM template builder.

Enforces an 80%+ coverage TDD workflow for feature builds, bug fixes, refactors, and API/component work by writing unit, integration, and Playwright E2E tests first, then implementing code, verifying coverage, and mocking downstream services.

Automatically scans modern API frameworks (Next.js, Express, FastAPI, Django) to generate comprehensive, ready-to-run test suites. It ensures complete coverage for critical areas including authentication, input validation (boundary/injection), error code matrices, pagination, file uploads, and rate limiting. Ideal for TDD, contract testing, and security audits.

Guides engineering teams working with AI-assisted code generation to prioritize planning, measurable coverage, resilient architectures, and behavior-focused reviews for safe, reliable delivery.

Ports existing Semgrep rules into new language variants, guiding applicability analysis, test-first creation, and validation so teams can expand rule coverage across polyglot codebases with confidence.

Parses Windows PowerShell Script Block Logs (Event ID 4104) to reconstruct multi-block scripts, detect obfuscated and encoded payloads, and flag living-off-the-land behaviors, helping SOC teams hunt threats and validate monitoring coverage with MITRE ATT&CK mappings.

Provides a structured guide to Rust testing practices, covering TDD-based unit, integration, async, property-based, mocking, and coverage approaches that keep code reliable from RED-GREEN-REFACTOR to cargo-llvm-cov reports.

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.

This guide implements the Red-Green-Refactor cycle, the core methodology of Test-Driven Development (TDD). It teaches developers to first write a failing test (RED), then implement the minimum required code to make the test pass (GREEN), and finally improve the structure and clarity of the code without changing its behavior (REFACTOR). Use this guide when mastering TDD, ensuring robust unit test coverage, or following best practices for writing resilient software.