В каталоге 183 730 навыков в 14 категориях.
Python code specialist for Django, FastAPI, Celery, Channels, pytest, uv, and Ruff. Use when reviewing, refactoring, or...
Python coding conventions and best practices. Use when writing, reviewing, or refactoring Python code, or when working w...
Python coding style enforcement (PEP standards, type hints, docstrings, modern patterns). Auto-loads when writing or rev...
Comprehensive Python programming guidelines based on Google's Python Style Guide. Use when Claude needs to write Python...
Coding conventions and best practices for Python based on the Google Python Style Guide, emphasizing readability, explic...
Python coding standards including line length (80 chars), naming conventions (snake_case, PascalCase), type hints, docst...
Python TDD workflow - write pytest tests first, implement, verify 80%+ coverage
Use this for the Python-specific realization of the SKELETON→RED→GREEN→REFACTOR TDD cycle — Protocol-based interface ske...
Test-driven development in Python using uv as the package manager. Covers the red-green-refactor cycle, vertical slicing...
python-telegram-bot library for building Telegram bots. Use for handlers, callbacks, inline keyboards, conversations, an...
Guides writing Python functional and end-to-end tests that validate application behavior. Use this skill when writing or...
Run and debug Python test pipelines using pytest or unittest. Handles dependency installation, test path selection, cove...
Python unit testing patterns for pytest, including test file structure, fixtures, mocks, and coverage strategy. Use when...
Use this when authoring integration tests against a real backend (PostgreSQL, Redis, Kafka, MinIO, NATS, MongoDB), debug...
Skill for the Tester Node to validate Python code via pytest subprocess (deterministic, no LLM).
Use when writing or reviewing tests for Python behavior, contracts, async lifecycles, or reliability paths. Also use whe...
Python testing patterns: pytest setup, fixtures, TDD, mocking, async tests, and integration tests
Write and run Python tests using pytest with fixtures, mocking, coverage, and the AAA pattern. Use when writing Python t...
使用pytest的Python测试策略，包括TDD方法、夹具、模拟、参数化和覆盖率要求。
Python testing best practices using pytest including fixtures, parametrization, mocking, coverage analysis, async testin...
Python test authoring and review with pytest. Use when writing, adding, generating, or reviewing Python tests or unit te...
pytest testing policies for Python projects. Use when writing or reviewing Python test code. Do NOT use for application...
Generate pytest tests for Python modules with parametrization, shared fixtures in conftest.py, and minimal mocking. Use...
| pytest Command | Purpose |
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
Apply backend pytest conventions: expects assertions, async fixtures, autospecced repository ports, test paths and layer...
Python testing patterns. Use when writing tests, setting up pytest, mocking dependencies, or reviewing test code.
Write and organize tests for scientific Python packages using pytest following Scientific Python community best practice...
Write focused, deterministic, well-documented pytest tests for AI-authored code.
Guides pytest testing with TDD, fixtures, and mocks. Use when adding Python test coverage, parametrizing pytest cases, o...
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements....
Complete Python testing system. PROACTIVELY activate for: (1) pytest fundamentals, (2) Fixtures and scopes, (3) Paramete...
General standards for writing reliable, isolated pytest tests in Python projects. Use this skill for test structure, fix...
This skill should be used when writing or reviewing Python tests. It enforces a dummy-class pattern over unittest.mock,...
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing...
Advanced pytest patterns for Python backend testing. Use when dealing with async tests, complex fixtures, mocking strate...
Guide pytest patterns and testing strategies when the user asks about Python testing, fixtures, mocking, or test organiz...
Comprehensive Python testing best practices, pytest conventions, test structure patterns (AAA, Given-When-Then), fixture...
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...
Port Python / NumPy / PyTorch code (Orbit Wars envs, agents, policies, rollout/PPO loops) to JAX, producing a `<name>_ja...
Python project tooling: pyproject.toml as the single source of truth, package managers (pip, Poetry, uv, pipenv), virtua...
When running, packaging, linting, formatting, or type-checking Python — use uv, Ruff, and ty with changes scoped to touc...
Fast Python type checking with ty (by Astral). Use when checking Python types, running type checks in CI, or setting up...
Complete Python type hints system. PROACTIVELY activate for: (1) Built-in generics (list[str], dict[str, int]), (2) Unio...
| Type | Syntax (3.9+) | Example |
Comprehensive reference guide for Python type hints, static type checking with mypy, modern type annotation patterns (PE...
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...
Python static typing and type annotations, checked with a static type checker — ty (Astral) or pyright (Microsoft/Pylanc...
Type hints are checked by a separate tool (`mypy`, `pyright`), never by CPython
Python type hints and type safety patterns. Triggers on: type hints, typing, TypeVar, Generic, Protocol, mypy, pyright,...
A skill for creating comprehensive Python unit tests using pytest. It provides guidance and templates for test structure...
Manage Python projects with uv. Use when creating Python projects, managing dependencies, running scripts, or installing...
Guidelines for Python dependency management using uv, the fast Python package installer and resolver.
Use when initializing a Python project or script, adding dependencies, or running commands with uv, especially to avoid...
Python single-file script development using uv and PEP 723 inline metadata. Prevents invalid patterns like [tool.uv.meta...
Manage Python virtual environments and dependencies. Use when setting up projects or installing packages.
Automatically manage Python virtual environments (.venv) in terminal commands. Always activate .venv before running Pyth...
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...
Configures Python development workspace for MQL5 integration. Use when setting up MetaTrader 5 Python API, configuring m...
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...
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...
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...
Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and auto...
create an initial PyTM-based threat model of your system when asked to perform a threat model
PyTorch deep learning development with transformers, diffusion models, and GPU optimization.
Fix common PyTorch bugs: percentile calculations, LayerNorm for Conv1d, buffer edge cases. Trigger when writing PyTorch...
PyTorch CUDA environment and performance guidance, with emphasis on CUDA 13 toolkit/driver requirements, PyTorch wheel c...
Distributed training strategies including DistributedDataParallel (DDP) and Fully Sharded Data Parallel (FSDP). Covers m...
Fully sharded data-parallel training for large models.
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...
High-level training framework for PyTorch that abstracts boilerplate while maintaining flexibility. Includes the Trainer...
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-G...
Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure...
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system,...
Deep learning with PyTorch - model training, GPU acceleration, and data science workflows
Guidance for creating standalone CLI tools that perform neural network inference by extracting PyTorch model weights and...
Guidance for recovering PyTorch model architectures from state dictionaries, retraining specific layers, and saving mode...
Build pytorch model trainer operations. Auto-activating skill for ML Training. Triggers on: pytorch model trainer, pytor...
Translate PyTorch implementations to Triton GPU kernels incrementally. Use when converting PyTorch code to Triton, optim...
PyTorch model training skill with custom training loops, gradient management, and GPU optimization.
Reproducible training loops: seeding, mixed precision, checkpoint and resume. Use when the task involves pytorch, python...
Knowledge base from "Python Tricks: The Book" by Dan Bader. Use when applying Bader's idioms for assertions, decorators,...
Routes pyts time-series loading, preprocessing, symbolic encoding, feature extraction, metrics, classification, and mult...
pytz timezone - use when working on related tasks
Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framewor...