What problem does it solve? Test suites often contain hidden quality issues — tests with no assertions, swallowed exceptions, flakiness from sleeps and wall-clock reads, or ordering dependencies — that give false confidence and erode trust in CI results. This Skill systematically audits existing test code and reports exactly what is wrong, where, and how to fix it. ## Core Features & Use Cases - Polyglot anti-pattern detection: Covers .NET (MSTest/xUnit/NUnit/TUnit), Python (pytest/unittest), JS/TS (Jest/Vitest/Mocha), Java (JUnit/TestNG), Go, Ruby, Rust, Swift, Kotlin, PowerShell (Pester), and C++ (GoogleTest/Catch2), with language-specific guidance loaded via extension files. - Severity-ranked reporting: Findings are grouped into Critical, High, Medium, and Low tiers with file/method/line locations and concrete before/after fixes, plus positive observations about what the tests do well. - Honest calibration: Built-in rules prevent false positives on idiomatic patterns like Go table-driven tests, pytest bare asserts, and distinct boundary-condition tests. - Use Case: Ask for an audit of a flaky pytest suite and receive a report flagging un-awaited async assertions as Critical, time.sleep synchronization as High, and magic values as Medium, each with a targeted fix. ## Quick Start Audit the test files in my project's tests directory for anti-patterns and rank the findings by severity.
