83,201 skills sorted by stars.
Advanced pytest patterns for Python backend testing. Use when dealing with async tests, complex fixtures, mocking strate...
pytest、TDD手法、フィクスチャ、モック、パラメータ化、カバレッジ要件を使用したPythonテスト戦略。
Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test fail...
| Type | Syntax (3.9+) | Example |
Python type safety with type hints, generics, protocols, and strict type checking. Use when adding type annotations, imp...
Use when Python's type system including type hints, mypy, Protocol, TypedDict, and Generics. Use when working with Pytho...
Use when defining or evolving public interfaces, schema boundaries, or pydantic usage in Python. Also use when annotatio...
A skill for creating comprehensive Python unit tests using pytest. It provides guidance and templates for test structure...
Run Python scripts with automatic dependency management using uv. Use this skill when you need to (1) run Python scripts...
Use when initializing a Python project or script, adding dependencies, or running commands with uv, especially to avoid...
Manage Python virtual environments and dependencies. Use when setting up projects or installing packages.
Python 虚拟环境自动化管理工具。当项目需要创建或管理 Python 虚拟环境（.venv）时使用此技能：检测现有环境、创建新环境、生成 requirements.txt、安装依赖包、配置 Git 忽略规则。
Use when preparing branches, commits, or PRs for Python changes — scoping work, running validation gates, and ensuring m...
Develop Python scripts and modules for building AI workflows and integrations. Use when coding data ingestion, transform...
Guided workflow for adding new features to Python projects. Use when planning a new feature implementation, when adding...
Debug functional issues in Python code using specs, logs, and observed behavior. Use when a feature isn't working as spe...
The model must use this skill when : 1. working within any python project. 2. Python CLI applications with Typer and Ric...
Configure pyproject.toml and Python packaging for distribution. Use when setting up a new Python package, when configuri...
Set up CI/CD pipeline for Python package publishing to PyPI. Use when preparing to publish a package, when setting up au...
Comprehensive Python code review checking patterns, types, security, and performance. Use when reviewing Python code for...
This skill should be used when the user asks to "design a test strategy", "plan test coverage", "create test architectur...
Essential Pythonic idioms and conventions. Apply when writing or reviewing Python code to ensure idiomatic patterns like...
Apply idiomatic Python patterns: list comprehensions, generators, context managers, decorators, dataclasses, walrus oper...
UTF-8 JSON file I/O utilities to avoid Windows encoding issues (CP-1252 vs UTF-8)
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, tra...
create an initial PyTM-based threat model of your system when asked to perform a threat model
Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and auto...
Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pip...
Core PyTorch fundamentals including tensor operations, autograd, nn.Module architecture, and training loop orchestration...
Configure and verify CUDA 13 readiness (toolkit, driver, and PyTorch wheel support), then run PyTorch CUDA with reliable...
Comprehensive guide for deploying PyTorch models to production, covering export formats, optimization techniques, and de...
Distributed training strategies including DistributedDataParallel (DDP) and Fully Sharded Data Parallel (FSDP). Covers m...
Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU of...
Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and di...
Library for Graph Neural Networks (GNNs). Covers MessagePassing layers, modular aggregation schemes, and handling large...
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-G...
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system,...