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Found 21 Skills
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.
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.
Modern Python development with uv, ruff, mypy, and pytest. Use when: - Writing or reviewing Python code - Setting up Python projects or pyproject.toml - Choosing dependency management (uv, poetry, pip) - Configuring linting, formatting, or type checking - Organizing Python packages Keywords: Python, pyproject.toml, uv, ruff, mypy, pytest, type hints, virtual environment, lockfile, package structure
GitHub workflow for ToolUniverse - push code safely by moving temp files, activating pre-commit hooks, running tests, and cleaning staged files. Use when pushing to GitHub, fixing CI failures, or cleaning up before commits.
Эксперт Python разработки. Используй для Python best practices, async, typing и ecosystem.
Python development with ruff, mypy, pytest - TDD and type safety
Python 3.13+ development specialist covering FastAPI, Django, async patterns, data science, testing with pytest, and modern Python features. Use when developing Python APIs, web applications, data pipelines, or writing tests.
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.
Extract raw price dataframe for a test case
Python 开发规范，包含 PEP 8 风格、类型注解、异常处理、测试规范等
Sets up Python development environment using UV for fast dependency management. Configures virtual environment, dependencies, testing (pytest), linting/formatting (ruff), and type checking (mypy). ALWAYS use UV - NEVER use pip directly. Use when starting work on Python projects, after cloning Python repositories, setting up CI/CD for Python, or troubleshooting Python environment issues.
Python development guidance with code quality standards, error handling, testing practices, and environment management. Use when writing, reviewing, or modifying Python code (.py files) or Jupyter notebooks (.ipynb files).