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Found 1,742 Skills
Python testing with pytest, coverage, fixtures, parametrization, and mocking. Covers test organization, conftest.py, markers, async testing, and TDD workflows. Use when user mentions pytest, unit tests, test coverage, fixtures, mocking, or writing Python tests.
現在の環境で適切なPythonコマンドを判別し、スクリプトを実行します。「Pythonコマンドを確認」「どのpythonを使う」「Python実行方法」といった依頼や、他のスキルからPythonスクリプトを実行する前に使用してください。
This skill should be used when the user asks to "create Pulumi Python project", "write Pulumi Python code", "use Pulumi ESC with Python", "set up OIDC for Pulumi", or mentions Pulumi infrastructure automation with Python.
Modern Python coaching covering language foundations through advanced production patterns. Use when asked to "write Python code", "explain Python concepts", "set up a Python project", "configure Poetry or PDM", "write pytest tests", "create a FastAPI endpoint", "run uvicorn server", "configure alembic migrations", "set up logging", "process data with pandas", or "debug Python errors". Triggers on "Python best practices", "type hints", "async Python", "packaging", "virtual environments", "Pydantic validation", "dependency injection", "SQLAlchemy models".
Comprehensive code reviewer for Java and Python implementations focusing on correctness, efficiency, code quality, and algorithmic optimization. Reviews LeetCode solutions, data structures, and algorithm implementations. Use when reviewing code, checking solutions, or providing feedback on implementations.
Modern Python asyncio, aiohttp, and concurrency patterns.
Python code security analysis, performance optimization, and maintainability assessment
Designs intuitive Python library APIs following principles of simplicity, consistency, and discoverability. Handles API evolution, deprecation, breaking changes, and error handling. Use when designing new library APIs, reviewing existing APIs for improvements, or managing API versioning and deprecations.
Optimizes Python library performance through profiling (cProfile, PyInstrument), memory analysis (memray, tracemalloc), benchmarking (pytest-benchmark), and optimization strategies. Use when analyzing performance bottlenecks, finding memory leaks, or setting up performance regression testing.
Use this skill when the user wants to manage Python projects, virtual environments, or dependencies using uv, including creating venvs, installing packages, syncing environments, or running Python tools.
Use when working with Python projects that use uv for dependency management, virtual environments, project initialization, or package publishing. Covers setup, workflows, and best practices for uv-based projects.
Build browser automation scripts using the Kernel Python SDK with Playwright and remote browser management.