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Found 1,370 Skills
Upgrade Python dependencies using uv, then run post-upgrade checks to ensure nothing is broken.
Analyze Python code for style improvements including naming, structure, nesting, and cognitive load reduction
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
Python data analysis with pandas, numpy, and analytics libraries
pytest testing patterns for Python. Triggers on: pytest, fixture, mark, parametrize, mock, conftest, test coverage, unit test, integration test, pytest.raises.
Эксперт Python разработки. Используй для Python best practices, async, typing и ecosystem.
Modern Python 3.12+ patterns your AI agent should use. Type hints, async/await, Pydantic v2, uv, match statements, and project structure.
Python performance profiling with cProfile, tracemalloc, and line_profiler. Use for identifying bottlenecks and memory issues. USE WHEN: user mentions "Python profiling", "cProfile", "memory profiling", asks about "Python performance", "tracemalloc", "line_profiler", "py-spy", "Python optimization", "Python memory leak" DO NOT USE FOR: Java/Node.js profiling - use respective skills instead
Use when scaffolding production-ready FastAPI services with uv, SQLAlchemy, Alembic, Postgres, Docker, and CI gates.
Write and audit Python code comments using antirez's 9-type taxonomy. Two modes - write (add/improve comments in code) and audit (classify and assess existing comments with structured report). Use when users request comment improvements, docstring additions, comment quality reviews, or documentation audits. Applies systematic comment classification with Python-specific mapping (docstrings, inline comments, type hints).
This skill should be used when the user asks to "implement dependency injection in Python", "use the dependency-injector library", "decouple Python components", "write testable Python services", or needs guidance on Inversion of Control, DI containers, provider types, and wiring in Python applications.
This skill should be used when the user asks to "configure ruff", "set up ruff linting", "use ruff formatter", "replace flake8 with ruff", or needs guidance on Python code quality with Ruff linting and formatting best practices.