Guide · Agent skill
How to use the Python Pro agent skill: setup, triggers and examples
Updated · written with AI from the project's own documentation and checked against our catalogue data
The python-pro agent skill is a set of instructions and reference notes that teaches an AI coding agent to write Python 3.11+ code the way a typing-focused specialist would. It is useful if you build or refactor Python projects and want full type hints, async/await for I/O work, and tests and linting run as part of the job. This guide explains what the skill does, how to install it, how to trigger it, and what to check before you trust its output.
Python ProJeffallan/claude-skills · MIT Download the skill Quick start
- 1Download the ZIP. Download the python-pro skill ZIP from this page.
- 2Unzip into a skills folder. Unzip it into ~/.claude/skills/ for personal use, or into .claude/skills/ in your project.
- 3Or upload in the Claude apps. In the Claude apps, go to Settings → Capabilities → Skills and upload the skill.
- 4Confirm your tools. Make sure Python 3.11+, mypy, pytest, black and ruff are available in your environment.
- 5Describe the Python task. Ask in plain language for typed code, async code, tests or a strict mypy setup, naming the file or module.
- 6Run the checks. Ask the agent to run mypy --strict, pytest, black and ruff, and to fix any reported issues.
What the python-pro skill makes the agent do
An agent skill is a folder with a SKILL.md file that tells the agent when and how to work on a certain kind of task. When python-pro is installed and relevant, the agent works like a Python specialist: it writes code with full type hints, uses async/await for I/O-heavy work, and follows dataclass, pathlib and context-manager conventions.
It can also set up a strict mypy configuration, write pytest test suites with fixtures and mocking, and run black and ruff to tidy the code. Reference notes on the type system, async patterns, the standard library, testing and packaging are loaded when the task calls for them.
- Type-annotated functions, classes and dataclasses
- Async/await patterns with asyncio, including task groups
- mypy strict configuration in pyproject.toml
- pytest tests with fixtures, parametrize and mocking
- Validation with mypy --strict, black and ruff
Install the python-pro skill
Download the ZIP for the python-pro skill from this page. Then choose one of two routes.
For a personal setup, unzip the skill into ~/.claude/skills/. For a single project, unzip it into the project's .claude/skills/ folder. In the Claude apps, you can instead upload the skill under Settings → Capabilities → Skills.
- Personal: unzip into ~/.claude/skills/
- Project only: unzip into .claude/skills/ inside your project
- Claude apps: Settings → Capabilities → Skills, then upload
Check what you need before you start
The skill assumes a Python 3.11+ environment. For the validation steps, mypy, pytest, black and ruff need to be installed. The async example uses httpx, but only if your project uses it.
The skill runs scripts and its validation steps execute code in your environment, so set it up in a project you are willing to let the agent run tools in.
- Python 3.11 or newer
- mypy, pytest, black and ruff installed for validation
- httpx only if your project uses it for async HTTP
- Runs scripts: yes. Uses network: no
Trigger the skill with natural requests
You do not need a special command. Describe the Python task in plain language and mention the relevant concern, such as type hints, async, tests or strict typing. The skill's description covers type hints, async/await patterns, dataclasses, dependency injection, logging configuration and structured error handling.
Requests that match the skill's triggers work best. Be specific about the file or module, and say whether you want tests and a mypy check included.
- "Add full type hints to src/myproject/config.py and make mypy --strict pass."
- "Convert this loop that calls three HTTP endpoints into an async function using asyncio.gather."
- "Write pytest tests with fixtures for the parser in utils.py, using a tmp_path fixture."
- "Replace this manual __init__ with a dataclass and validate the port number."
- "Set up a strict mypy section in pyproject.toml for this Python 3.11 project."
Read the output: what the agent produces
The skill's output template asks for a module file with complete type hints, a test file with pytest fixtures, a type-checking confirmation that mypy --strict passes, and a short explanation of the Pythonic patterns used. Read the explanation, because it tells you why the agent chose a dataclass, a context manager or an async pattern.
A clean mypy run reports a success line such as Success: no issues found in 12 source files. Any reported error must be resolved before the work counts as finished, so ask the agent to re-run the checks if it did not show a clean result.
- Module file with type hints
- Test file with pytest fixtures
- mypy --strict result
- Explanation of patterns used
mypy --strictSafety notes: scripts and tools
Because the workflow runs mypy, pytest, black and ruff, those commands execute in your environment. Review the project and the commands before you approve them, and do not run the skill on code you have not backed up or on a machine holding secrets you have not protected.
The skill's own rules say not to hardcode secrets or configuration, so check the output anyway. If you need to review every line without the agent running tools, this skill is not the right fit.
- Validation runs code, so use a project you control
- Check that secrets and configuration are not hardcoded
- Uses network: no, according to the skill listing
Tips for better results
Give the agent the Python version and the tools your project already uses, such as Poetry or pyproject.toml. The skill's packaging notes cover pyproject.toml and src layouts, so naming your layout helps. Ask for tests alongside the code, since the skill targets coverage above 90% with pytest.
Keep changes small. Ask for one module or one function at a time so mypy and pytest errors stay easy to trace.
- Name your Python version and existing tools
- Ask for tests in the same request
- Work one module at a time
- Ask the agent to re-run mypy, pytest, black and ruff after edits
What people use it for
- Adding full type hints and a strict mypy config to an existing Python 3.11+ package
- Converting sequential I/O calls into async/await code with asyncio.gather
- Writing pytest tests with fixtures, tmp_path and parametrize for a parser or config loader
- Replacing manual __init__ methods with dataclasses that validate their fields
- Tidying a module with black and ruff before a code review
Frequently asked questions
How do I install the python-pro skill?
Download the ZIP from this page and unzip it into ~/.claude/skills/ for personal use, or into .claude/skills/ inside a project. In the Claude apps, you can upload it under Settings → Capabilities → Skills.
What do I need to use python-pro?
You need a Python 3.11+ environment, and mypy, pytest, black and ruff installed for the validation steps. httpx is needed only if your project uses it for the async example.
Is the python-pro skill free?
The skill is listed under the MIT licence. This page does not state pricing, so check the licence file in the source repository for the exact terms.
Does python-pro work with Python versions older than 3.11?
Not as intended. The guidance assumes Python 3.11+ features, so projects on older versions are not a good fit.
Does the skill need internet access?
The skill listing says it does not use the network. It does run scripts, such as mypy, pytest, black and ruff, in your environment.
How is python-pro different from just asking an AI for Python code?
The skill gives the agent a fixed workflow and reference notes on typing, async, the standard library, testing and packaging, and asks it to run mypy --strict, pytest, black and ruff. A general prompt does not include those checks unless you ask for them each time.
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Our verdict
Use python-pro if you build or refactor Python 3.11+ projects and want stricter typing, pytest suites and ruff/black checks handled consistently. Pick something else if your project runs on an older Python, or if you need to review every line without the agent executing tools in your environment.
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