What problem does it solve? Test suites often contain tests that pass but verify nothing, are flaky, or are hard to maintain, giving teams false confidence in their code. This Skill audits existing test files across many languages and frameworks, detecting anti-patterns and reporting them ranked by severity so you know exactly what to fix first. ## Core Features & Use Cases - Severity-ranked detection: Finds Critical issues (no assertions, swallowed exceptions, self-referential assertions, missing await on async assertions), High issues (flakiness from Thread.Sleep, DateTime.Now, shared state, over-mocking), and Medium/Low issues (poor naming, magic values, duplicate tests). - Multi-language support: Works with .NET (xUnit/NUnit/MSTest), Python/pytest, TypeScript/Jest, Java/JUnit, Go, Ruby/RSpec, Rust, C++, and PowerShell/Pester via language-specific extension guidance. - Honest calibration: Avoids false positives by recognizing idiomatic patterns like Go table-driven tests and pytest bare asserts, and leads with positive observations when tests are well-written. - Use Case: Point the Skill at a flaky .NET test project and receive a report showing which tests use Thread.Sleep for synchronization, which assert nothing, and concrete before/after fixes prioritized by severity. ## Quick Start Ask the AI to audit the tests in your project directory for anti-patterns and report the findings ranked by severity.
