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Found 67 Skills
Convert a Streamlit app to a marimo notebook
Develop Python applications using modern patterns, uv, functional-first design, and production-first practices. Use this whenever working with .py files, pyproject.toml, uv commands, pip/pip3, poetry, virtualenv/venv, inline script metadata, or Python tooling like pytest, mypy, ruff, asyncio, itertools, functools, or dataclasses. If the task involves running Python, managing Python dependencies, creating environments, or building Python packages, load this skill and prefer uv-oriented workflows.
Use this skill when you need to work with sentry through its generated async Python app, call its MCP-backed functions from code, or inspect available functions with the mcp-skill CLI.
Python expert for stdlib, packaging, type hints, async/await, and performance optimization
Comprehensive software development planning and implementation skill. Triggers when: Creating new Python software with CLI/GUI/Web interfaces, planning software architecture and modules, designing scientific or engineering applications, setting up bilingual documentation and PyPI publishing, or needing academic research-based feature design. Capabilities: Pre-development planning and research, multi-interface design (CLI + PySide6 GUI + Flask Web), scientific visualization with pyqtgraph, academic literature-based feature design, sample data and test documentation generation, bilingual README with structured sections, GPLv3 licensing and PyPI publishing setup.
Before running Python scripts or installing packages, check for existing virtual environments and reuse them if found. If no virtual environment exists, ask the user to choose: (1) Create new venv in current directory (recommended), (2) Use system Python directly, or (3) Create venv at custom path. This applies to: running .py files, using pip/uv pip install, or any task requiring third-party packages. Exceptions: simple one-liners using only Python standard library.
Automatically add or improve type annotations in legacy Python code. Use to improve code readability, IDE support, and catch type errors early.
Design structured logging systems with context propagation. Use to ensure Python applications are observable and logs are machine-readable.
Install Holoscan SDK v4.3+ via Conda in a CUDA 13 environment. Use for Conda installs; redirect CUDA 12 hosts to container/wheel.
Python development guidelines and best practices. Use when working with Python code.
Modern Python development with uv (10-100x faster package manager) and ruff (extremely fast linter/formatter). Use when managing Python projects, dependencies, virtual environments, installing packages, linting code, or formatting Python files. Triggers on phrases like "uv install", "ruff check", "python package manager", "format python code", or working with pyproject.toml files.
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).