A skill is a set of instructions packaged as a SKILL.md file that an AI agent reads to learn a new workflow. Python-specific skills teach AI agents to follow Python conventions, use the right testing frameworks, handle virtual environments, and write idiomatic code.
> Quick Answer: The best skills for Python developers cover pytest test generation, type hint enforcement, virtual environment management, Django/FastAPI conventions, and Python-specific code review. All use the SKILL.md format and work across Claude Code, OpenClaw, Codex CLI, and other compatible agents. Browse them at agensi.io/skills.
Why do Python developers need specific skills?
Generic AI coding skills are language-agnostic. That's fine for simple tasks, but Python has conventions that generic instructions miss: PEP 8 formatting, type hints (PEP 484), virtual environment management, the difference between pytest and unittest, Poetry vs pip vs uv, and Django vs FastAPI vs Flask patterns.
A Python-specific skill encodes these choices so the agent produces code that matches your stack without being told every time.
What are the best Python testing skills?
The best Python testing skills detect whether you use pytest, unittest, or nose, and generate tests accordingly. They handle pytest fixtures, parametrized tests, mock patterns, and conftest.py conventions.
Key features to look for: automatic fixture detection (reads your existing conftest.py), proper assertion patterns (pytest's plain `assert` vs unittest's `self.assertEqual`), and coverage-aware generation that targets untested functions.
What are the best Python code review skills?
Python code review skills check for Pythonic patterns — list comprehensions over loops where appropriate, proper exception handling (no bare `except:`), type hint coverage, import ordering (isort conventions), and f-string usage over `.format()`.
The code-reviewer skill on Agensi works for Python projects. For Python-specific review criteria, build a custom skill that includes your team's Python standards.
What are the best Django and FastAPI skills?
Framework-specific skills handle the patterns that generic agents get wrong:
Django: Model field choices, queryset optimization (avoiding N+1), migration file validation, view/serializer patterns, template tag conventions.
FastAPI: Pydantic model design, dependency injection patterns, async endpoint best practices, OpenAPI schema generation.
A skill that knows your framework's conventions produces code that follows them automatically.
How do I build a Python-specific skill?
```yaml
---
name: python-standards
description: Use when writing Python code, generating Python functions, or reviewing Python files.
---
# Python Standards
Environment
- Python 3.11+ - Package manager: uv (not pip directly) - Virtual env: .venv in project rootStyle
- Follow PEP 8 - Use type hints on all function signatures - Use f-strings, not .format() or % - Prefer pathlib over os.pathTesting
- Use pytest (not unittest) - Fixtures in conftest.py - File naming: test_*.py - Parametrize when testing multiple inputsImports
- stdlib → third-party → local (isort default) - Absolute imports only ```This works in any SKILL.md-compatible agent. Install to your agent's skills directory and start a new session.
---
*Browse Python-compatible skills for any AI coding agent on Agensi.*
