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Found 127 Skills
Python/pytest TDD specialist for test-driven development workflows. Use when writing tests, auditing test quality, running pytest, or generating test reports. Integrates with uv and pyproject.toml configuration.
Galaxy testing with pytest and run_tests.sh - run/write unit, integration, API, selenium tests. Use for: test execution, test failures, pytest errors, ApiTestCase patterns, test fixtures, writing new tests, debugging test failures, test/integration, lib/galaxy_test/api tests. CRITICAL: Always use ./run_tests.sh, never pytest directly.
Performance and load testing patterns — k6 load tests, Locust stress tests, pytest execution optimization (xdist parallel, plugins), test type classification, and performance benchmarking. Use when writing load tests, optimizing test execution speed, or setting up pytest infrastructure.
Guide for selecting and executing the correct pytest suites (unit, integration, redis, R2, routing rules, magic link) with environment setup and coverage expectations.
Automated test generation, review, and execution for pytest-based projects. Auto-activates on keywords test, coverage, pytest, unittest, integration test, e2e, performance, benchmark, security testing. Routes to specialized testing workflows based on user intent.
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.
Consult this skill for Python testing implementation and patterns. Use when writing unit tests, setting up test suites, implementing TDD, configuring pytest, creating fixtures, async testing, writing integration tests, mocking dependencies, parameterizing tests, setting up CI/CD testing. Do not use when evaluating test quality - use pensive:test-review instead. DO NOT use when: infrastructure test config - use leyline:pytest-config.
factory_boy test data generation specialist. Covers Factory, DjangoModelFactory, SQLAlchemyModelFactory, all field declarations (Faker, LazyAttribute, Sequence, SubFactory, RelatedFactory, post_generation, Trait, Maybe, Dict, List), batch creation, pytest integration, and Celery task testing patterns. USE WHEN: user mentions "factory_boy", "test factory", "DjangoModelFactory", "SQLAlchemyModelFactory", asks about "test data generation", "factory traits", "SubFactory", "factory fixtures". DO NOT USE FOR: pytest internals - use `pytest`; Django setup - use `pytest-django`; Hypothesis property testing - use `pytest` with Hypothesis
Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
Sets up async tests with proper fixtures and mocks using pytest-asyncio patterns. Use when testing async functions, creating async fixtures, mocking async services, or handling async context managers. Covers @pytest_asyncio.fixture, AsyncMock with side_effect, async generator fixtures (yield), and testing async context managers. Works with Python async/await patterns, pytest-asyncio, and unittest.mock.AsyncMock.
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.