testing-patterns
This skill has been split into five specialized sub-skills, each addressing a distinct testing need. Choose testing-unit for isolated logic, testing-e2e for browser automation, testing-integration for cross-boundary APIs and databases, testing-llm for AI evaluation, or testing-perf for load and performance work.
Testing Patterns directs you to specialized sub-skills for unit, end-to-end, integration, LLM, and performance testing.
AI-generated summary based on this skill's SKILL.md
Install
yonatangross/orchestkit/testing-patterns · repository language: TypeScript
git clone https://github.com/yonatangross/orchestkit
cp -r orchestkit/src/skills/testing-patterns ~/.claude/skills/testing-patternsnpx skillfed install yonatangross/orchestkit/testing-patternsFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What testing patterns does testing-patterns cover?
testing-patterns has been split into five specialized sub-skills to match your specific needs. Choose testing-unit for isolated logic verification, testing-e2e for browser automation and user workflows, testing-integration for cross-boundary APIs and databases, testing-llm for AI output evaluation, or testing-perf for load and performance analysis. Each sub-skill focuses on patterns and best practices for its domain.
How do I write tests for my specific use case?
testing-patterns guides you to the right testing approach by breaking down five distinct scenarios. For unit testing patterns and best practices, use testing-unit. For end-to-end browser testing, use testing-e2e. For integration or API testing, use testing-integration. For LLM output evaluation, use testing-llm. For performance and load testing, use testing-perf. Each sub-skill contains targeted patterns for its scope.
What test automation frameworks does testing-patterns support?
testing-patterns directs you to specialized sub-skills rather than covering all frameworks in one place. testing-e2e includes Playwright patterns for browser automation. testing-integration covers API testing approaches. testing-perf addresses load testing with k6 and similar tools. testing-unit focuses on pytest patterns and unit testing strategies. testing-llm handles AI evaluation frameworks. Consult the relevant sub-skill for your framework.
Can testing-patterns help with LLM testing and evaluation?
testing-patterns recommends the testing-llm sub-skill for evaluating and testing LLM outputs. That specialized skill covers patterns, best practices, and strategies specific to AI model evaluation, rather than mixing LLM concerns with traditional testing approaches. Use testing-llm when your primary goal is assessing language model performance and correctness.
How do I choose between unit, integration, and end-to-end tests?
testing-patterns helps you find the right testing approach by offering five focused sub-skills. Use testing-unit for isolated logic and fast feedback. Use testing-integration for cross-boundary interactions with APIs and databases. Use testing-e2e for full user workflows through the browser. Use testing-perf for load and performance concerns. Use testing-llm for AI output validation. Each sub-skill explains when and why to apply its patterns.
Is testing-patterns available under an open-source license?
Yes, testing-patterns is released under the MIT license, allowing free use, modification, and distribution in both open-source and commercial projects.
SKILL.md
rendered from the published skill — quoted content, verbatim
Testing Patterns (Redirect)
> This skill was split into 5 focused sub-skills in v7.2.0. Use the appropriate sub-skill below.
Sub-Skills
| Sub-Skill | Focus | When to Use |
|---|---|---|
ork:testing-unit |
Unit tests, AAA pattern, fixtures, mocking, factories | Isolated business logic tests |
ork:testing-e2e |
Playwright, page objects, visual regression, a11y | Browser-based end-to-end tests |
ork:testing-integration |
API endpoints, database, contract testing | Cross-boundary integration tests |
ork:testing-llm |
LLM mocking, DeepEval/RAGAS, structured output | AI/ML evaluation and testing |
ork:testing-perf |
k6, Locust, |
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src/skills/testing-patterns/SKILL.md
src/skills/testing-patterns/rules/_sections.md
src/skills/testing-patterns/rules/assertion-quality.md
src/skills/testing-patterns/rules/test-isolation.md
src/skills/testing-patterns/test-cases.json