Total 50,523 skills, Testing & QA has 1781 skills
Showing 12 of 1781 skills
Quick pragmatic review of .NET test code for anti-patterns that undermine reliability and diagnostic value. Use when asked to review tests, find test problems, check test quality, or audit tests for common mistakes. Catches assertion gaps, flakiness indicators, over-mocking, naming issues, and structural problems with actionable fixes. Use for periodic test code reviews and PR feedback. For a deep formal audit based on academic test smell taxonomy, use exp-test-smell-detection instead. Works with MSTest, xUnit, NUnit, and TUnit.
Vitest unit testing patterns with React Testing Library. Trigger: When writing unit tests for React components, hooks, or utilities.
Developer Test Auto-Completion Skill - Generate high-quality unit tests for functions and classes, analyze coverage blind spots and generate high-value supplementary tests to improve effective coverage.
Run, watch, debug, and extend OpenClaw QA testing with qa-lab and qa-channel. Use when Codex needs to execute the repo-backed QA suite, inspect live QA artifacts, debug failing scenarios, add new QA scenarios, or explain the OpenClaw QA workflow. Prefer the live OpenAI lane with regular openai/gpt-5.4 in fast mode; do not use gpt-5.4-pro or gpt-5.4-mini unless the user explicitly overrides that policy.
Detect non-deterministic (flaky) tests by reading CI run logs or test result history. Aggregates pass rates per test, identifies intermittent failures, recommends quarantine or fix, and maintains a flaky test registry. Best run during Polish phase or after multiple CI runs.
You are **Performance Benchmarker**, an expert performance testing and optimization specialist who measures, analyzes, and improves system performance across all applications and infrastructure. Yo...
Evaluate test coverage and fill real gaps with high-value tests.
Use when writing or reviewing Jetpack Compose UI tests, screenshot tests, previews, semantics assertions, fake image loading, keyboard input, focus assertions, or tests for plain state-driven UI composables.
Comprehensive testing doctrine for software and AI systems — covers positive patterns, anti-patterns, gates for coding agents writing tests, CI discipline, and an LLM/agent evaluation primer. Use when authoring or reviewing tests, adding mocks, deciding test placement, generating tests via agents, debugging flaky CI, designing eval suites for LLM features, or rebuilding a brittle test suite. Contains 12 positive patterns (selector hierarchy, table-driven, builders, real-system gates), 25 anti-patterns across Brittleness, Flakiness, Mock-misuse, Process, and AI-specific families, 7 mandatory gates for agents writing tests, flaky-test taxonomy with quarantine workflow, contract / property / mutation testing patterns, and an oracle-ladder primer for LLM-as-judge and agent eval. Language-agnostic — pseudo-code only. Don't use for general code review, library-specific debugging unrelated to tests, non-testing CI pipeline design, or production observability.
Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey completeness, then summarizes the pre-error context. Replaces blind session picking from potentially hundreds of linked recordings.
Deep formal test smell audit based on academic research taxonomy (testsmells.org). Detects 19 categorized smell types — conditional logic, mystery guests, sensitive equality, eager tests, and more — with calibrated severity and research-backed remediation. Use for comprehensive test suite health assessments. For a quick pragmatic review, use test-anti-patterns instead. DO NOT USE FOR: writing new tests (use writing-mstest-tests), evaluating assertion quality specifically (use assertion-quality), or finding test duplication and boilerplate (use exp-test-maintainability).
Used when implementing any feature or fixing bugs, before writing the implementation code