Loading...
Loading...
Found 94 Skills
Use when implementing or repairing Univer package-local project behavior with assertions.ts, Facade Migration Packs, univer sac apply, univer sac verify, or verify-report loops.
Use this skill when the user wants to manage data quality in DataHub: create or run assertions, check assertion outcomes, raise or resolve incidents, create notification subscriptions, or diagnose health problems across their estate. Triggers on: "create assertion", "run assertion", "check quality", "data quality", "health check", "raise incident", "resolve incident", "subscribe to", "failing assertions", "active incidents", or any request involving data quality, assertions, incidents, or quality notifications.
PHPUnit testing framework conventions and practices. Invoke whenever task involves any interaction with PHPUnit — writing tests, configuring PHPUnit, data providers, mocking, assertions, debugging test failures, or coverage.
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Provides exact patterns for diagnosing and fixing automatic batching regressions in React 18 class components. Use this skill whenever a class component has multiple setState calls in an async method, inside setTimeout, inside a Promise .then() or .catch(), or in a native event handler. Use it before writing any flushSync call - the decision tree here prevents unnecessary flushSync overuse. Also use this skill when fixing test failures caused by intermediate state assertions that break after React 18 upgrade.
.NET Testing Basic Skills Overview and Guidance Hub. Triggered when users ask general testing questions such as "How to write .NET tests", "Introduction to .NET testing", "What testing tools are needed", "Testing best practices", "Learn testing from scratch", etc. It will recommend suitable sub-skill combinations based on specific needs, covering 19 basic skills including testing fundamentals, test data, assertions, mocking, special scenarios, etc. Keywords: dotnet testing, .NET testing, testing introduction, how to write tests, testing best practices, unit test, unit testing, xunit, 3A pattern, FIRST principles, assertion, assertion, mock, stub, NSubstitute, test data, AutoFixture, Bogus, validator, FluentValidation, TimeProvider, IFileSystem, code coverage, ITestOutputHelper, test naming
React component and hook testing patterns with Testing Library and Vitest. Use when writing tests for React components, custom hooks, or data fetching logic. Covers component rendering tests, user interaction simulation, async state testing, MSW for API mocking, hook testing with renderHook, accessibility assertions, and snapshot testing guidelines. Does NOT cover E2E tests (use e2e-testing) or TDD workflow enforcement (use tdd-workflow).
Comprehensive Go testing strategies including table-driven tests, testify assertions, gomock interface mocking, benchmark testing, and CI/CD integration
Use when writing, reviewing, or refactoring vitest tests. Load when you see *.test.ts or *.spec.ts files, nested describe blocks, loose assertions (toBeTruthy), over-mocking, slow tests, or async testing needs. Covers AAA pattern, parameterized tests, test doubles hierarchy, mock cleanup, test isolation, and performance optimization. Keywords include vitest, testing, TDD, assertions, mocks, stubs, fakes, spies, beforeEach, describe, it, expect, vi.mock, it.each.
Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.
Systematically investigate social media claims and viral content. Use when fact-checking complex claims, when decomposing multi-part assertions, or when investigating narratives that mix facts with interpretation.
Verify and validate AI output before it reaches users. Use when you need guardrails, output validation, safety checks, content filtering, fact-checking AI responses, catching hallucinations, preventing bad outputs, quality gates, or ensuring AI responses meet your standards before shipping them. Covers DSPy assertions, verification patterns, and generate-then-filter pipelines.