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Found 24 Skills
Consult this skill for async Python patterns and concurrency. Use when building async APIs, concurrent systems, I/O-bound applications, implementing rate limiting, async context managers. Do not use when CPU-bound optimization - use python-performance instead. DO NOT use when: testing async code - use python-testing async module.
Auto-activate for polyfactory, ModelFactory, DataclassFactory, MsgspecFactory, AttrsFactory, Use, register_fixture, pytest plugin, __random_seed__, or coverage(). Not for production seeding.
Guides the agent through running and writing Python tests with pytest. Triggered when users say "run tests", "write a test", "test this function", "add unit tests", "run pytest", "check test coverage", "debug failing test", "create test fixtures", "mock a dependency", or mention pytest, pytest-asyncio, pytest-cov, testing, unit tests, integration tests, test coverage, or test-driven development.
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.
Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices. Use for Python projects, APIs, data processing, or automation scripts.
Test-driven development workflow enforcement for Python and React projects. Use when the user requests TDD, test-first development, or red-green-refactor methodology. Enforces strict cycle: write ONE failing test -> implement minimum code to pass -> refactor while green -> repeat. Applies to both backend (pytest) and frontend (Testing Library). Changes agent behavior to write tests before code. Does NOT provide testing patterns (use pytest-patterns or react-testing-patterns for how to write tests).
Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.
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.
Generate pytest test cases for Python functions and classes
Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.
pytest - Python's most powerful testing framework with fixtures, parametrization, plugins, and framework integration for FastAPI, Django, Flask
Use before writing or editing any Python code — scripts, functions, bug fixes, cron jobs, data-processing one-offs, or additions to an existing .py file — even if the request sounds quick, casual, or "just a simple script." Applies whether the user names a .py file, describes what the script should do, or asks you to add/fix a function in Python. Covers required standards: type hints, no global variables, logging instead of print, wrapping any I/O (HTTP, DB, subprocess, file) in try/except, commenting the why not the what, writing a real test, and where to place design docs. Does not apply to conceptual Python questions with no code to write (e.g. explaining language features, comparing list vs tuple, explaining what an existing traceback means when the user hasn't asked for a fix, package install help, or learning-resource recommendations), and does not apply to non-Python languages.