Find the perfect capability for your agent.
Develop Python applications using modern patterns, uv, functional-first design, and production-first practices. Activate when working with .py files, pyproject.toml, uv commands, or user mentions Python, itertools, functools, pytest, mypy, ruff, async, or functional programming patterns.
Advanced usage of uv, the extremely fast Python package and project manager from Astral. Use this skill when working with uv for project management (uv init, uv add, uv run, uv lock, uv sync), workspaces and monorepos, dependency resolution strategies (universal, platform-specific, constraints, overrides), Docker containerization, PEP 723 inline script metadata, uvx tool execution, Python version management, pip interface migration, pyproject.toml configuration, or any advanced uv workflow. Covers workspaces, resolution strategies, Docker best practices, CI/CD integration, and migration from pip/poetry/pipenv.
Standard workflow for Python dependency management. Use this skill when we need to: (1) Install or remove Python packages, (2) Create or sync virtual environments, (3) Run Python scripts or tests, (4) Debug dependency conflicts, or (5) Initialize new Python projects.
Use whenever working on a python project. Manage Python projects using uv package manager with modern Python project structure.
Setup and manage Python environments using uv. Initialize projects, create virtual environments, install packages, and manage dependencies with pyproject.toml. Use when setting up new Python projects or managing dependencies.
Sets up a new Python library project using uv in the current directory. Creates project structure, installs dev dependencies, and optionally configures git remote. Use when the user wants to initialise a Python library, package, or project with uv.
Generate standalone Python scripts (not packaged projects) with PEP 723 inline metadata, a uv run shebang, and Typer CLI scaffolding. Use when the user wants a one-off executable script, automation tool, or runnable file that should declare dependencies inline and not live inside a package or project.
Create distributable Python packages with pyproject.toml, setup.py, and PyPI publishing. WHEN: Packaging Python libraries, creating pyproject.toml/setup.py, building CLI tools with entry points, publishing to PyPI, configuring package metadata. WHEN NOT: Managing dependencies (use python-uv-package-manager), writing application code, creating virtual environments.
Use when standardizing Python research code dependencies, environment setup, and lockfiles.
Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.
Python environment setup with uv, shared utilities, and script structure guidelines.
Use when writing async code, using asyncio.gather, handling concurrent operations, or when user mentions "asyncio", "async", "await", "gather", "concurrent", "parallel tasks", "fail-fast", "timeout", "race condition", "cancellation".
Use when improving run configuration, seeding, and reproducibility for Python research code.
Master Python asyncio, concurrent programming, and async/await patterns for high-performance FastAPI applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
自动化流程与脚本专家，擅长使用 Python, PowerShell, Shell 及各类工具实现任务自动化。
繰り返し作業の自動化スクリプト生成スキル。Shell、Python、PowerShell、Node.jsスクリプトを生成。ファイル操作、データ処理、API連携、CI/CD、バックアップ、監視、レポート生成を自動化。
在沙盒环境中执行Python代码，用于数据分析、可视化和生成Excel、Word、PDF等文件。支持数据清洗、统计分析、机器学习、图表生成、文档自动化等复杂工作流。
CLI testing strategies and patterns for Node.js (Jest) and Python (pytest, Click.testing.CliRunner). Use when writing tests for CLI tools, testing command execution, validating exit codes, testing output, implementing CLI test suites, or when user mentions CLI testing, Jest CLI tests, pytest CLI, Click.testing.CliRunner, command testing, or exit code validation.
Compact Snakemake workflow patterns. Keep rules short, complex logic in Python modules.
