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Found 143 Skills
Pytest testing patterns for Python. Trigger: When writing Python tests - fixtures, mocking, markers.
Testing use cases and application services: use case testing with mocked gateways, DTO testing, application exception testing, orchestration testing, mocking at adapter boundaries. Coverage target: 85-90%. Use when: Testing use cases, testing application services, testing DTOs and data transformation, testing error handling in use cases, mocking external dependencies at layer boundaries.
Creates pytest fixtures following project patterns including factory fixtures, async fixtures, and multi-layer organization. Use when setting up test fixtures, creating test data, organizing test utilities, or structuring conftest.py files. Works with Python test files, pytest configuration, and .py test utilities.
Auto-activate for pytest_databases, Docker DB fixtures, PostgreSQL/pgvector/AlloyDB Omni/MySQL/Oracle/MSSQL/CockroachDB/Yugabyte/MongoDB/GizmoSQL/Redis/Spanner/BigQuery/Azurite/MinIO tests. Not for mocked DBs.
This skill should be used when the user asks to "write pytest tests", "set up pytest best practices", "configure pytest", "write fixtures", or needs guidance on pytest testing patterns and project structure.
How to test domain models effectively: value object testing (immutability, validation), entity testing (identity, business logic), domain exception testing, aggregate testing, high coverage patterns (95%+), and testing invariants and constraints. Use when: Testing domain layer code, validating value objects, testing entities with business logic, ensuring domain invariants, or achieving 95%+ coverage on domain models.
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
Use when building Python 3.11+ applications requiring type safety, async programming, or production-grade patterns. Invoke for type hints, pytest, async/await, dataclasses, mypy configuration.
Write comprehensive unit tests with high coverage using testing frameworks like Jest, pytest, JUnit, or RSpec. Use when writing tests for functions, classes, components, or establishing testing standards.
Creates test infrastructure with Vitest, xUnit, and pytest
Run code quality checks (ruff, mypy, pytest) and optionally simplify code. This skill should be used when the user wants to check code quality, run linters, run tests, or simplify recently modified code. Triggered by /lint, /check, or /code-quality commands.