Guide · Agent skill
How to use the Python Expert agent skill (python-expert)
Updated · written with AI from the project's own documentation and checked against our catalogue data
The python-expert skill is a set of written guidance that tells an AI agent to work like a senior Python developer. It covers the standard library, packaging, type annotations, async/await and performance work. This guide explains what the skill changes, how to install it from a ZIP file, how to ask for help in a way that triggers it, and what to watch for.
Python ExpertRightNow-AI/openfang · Apache-2.0 Download the skill Quick start
- 1Download the ZIP. Get the python-expert ZIP from this page. It contains SKILL.md.
- 2Unzip into a skills folder. Extract it into ~/.claude/skills/ for personal use, or into the project's .claude/skills/ folder for one project.
- 3Or upload in the Claude apps. In the Claude apps, open Settings, go to Capabilities, and upload the skill under Skills.
- 4Ask for Python work in plain language. Request code, a review, packaging help or async work, and mention your Python version and any constraints.
- 5Check the output against the conventions. Look for type annotations, pytest tests, None defaults and specific exception handling in what the agent produces.
- 6Run and test the code yourself. The skill does not run software, so execute and test the generated code in your own Python environment.
What does the Python Expert skill make the agent do?
When you ask for Python code or a review, the agent follows a set of conventions drawn from its SKILL.md file. It aims for PEP 8 style, type annotations on public function signatures, and tests written with pytest. It prefers pyproject.toml as the single source of metadata, dependencies and tool configuration, and it recommends profiling with cProfile or line_profiler before optimizing.
The skill also steers the agent away from common mistakes: mutable default arguments, bare except clauses, and blocking calls inside async code. It is guidance only. It adds no tools or scripts of its own, so the agent still does the work using whatever it already has access to.
- Type-annotated public functions, with typing generics and Protocol where useful
- Dataclasses for simple value objects, pydantic for validated data
- Dependency workflows with uv or pip-compile, and virtual environments via python -m venv .venv or uv venv
- Pitfall checks: no mutable defaults, no bare except, asyncio.to_thread() for blocking work
How do you install the python-expert skill?
Download the ZIP for the skill from this page. The package contains a single file, SKILL.md. Unzip it so the skill folder sits in one of the locations below. Claude Code looks for skills in ~/.claude/skills/ for your user account, or in a project's .claude/skills/ folder for that project only.
If you use the Claude apps instead, open Settings, go to Capabilities, and upload the skill under Skills.
- Personal install: unzip into ~/.claude/skills/
- Project install: unzip into the project's .claude/skills/ folder
- Claude apps: Settings → Capabilities → Skills, then upload the skill
How do you trigger the skill with natural requests?
You do not need a special command. Ask for Python work in plain language and the agent can apply the skill when the request matches its description: Python code, standard library, packaging, type hints, async/await or performance. Saying the topic explicitly, such as asking for a Python code review or an async version of a function, makes the match clearer.
Be specific about the outcome you want. The skill guides style and structure, so mention the things you care about, like whether the code must run on a particular Python version.
- Write a function that ... with type hints and a pytest test
- Review this module for mutable default arguments and bare except clauses
- Convert these sequential HTTP calls to asyncio.gather()
- Set up pyproject.toml and a uv-based dependency workflow for this project
- Profile this function before we change anything
What examples show the skill in use?
The skill supplies conventions, so the clearest examples are requests where those conventions matter. A reviewer can check whether the agent followed them.
Ask for a function that takes a list and returns a result, and check that the parameter default is None rather than a list literal, with the body creating the list. Ask for a background task, and check that the agent uses asyncio.create_task() rather than running blocking calls directly on the event loop.
- Refactor a function with items=[] so it uses None as default
- Replace a broad except Exception with the specific errors the code can raise
- Add a Protocol-based repository with get(), save() and delete() methods for testing
- Build a small CLI with typer, using type hints for arguments
What do you need before using it?
The skill lists no required tools, scripts or network access. It runs no scripts and uses no network. Its guidance assumes Python 3.10 or later and PEP 8 style. If your project uses an older Python or a different style standard, tell the agent so it does not suggest features your version lacks.
You still need a Python environment to run the code the agent writes. The skill does not install Python or build an application for you.
- Python 3.10+ for the features the guidance assumes
- Your own project environment to run and test the output
- Nothing else is required by the skill itself
What safety points should you know?
The skill runs no scripts and makes no network calls, so installing it does not run code on your machine. Its content is plain text instructions in SKILL.md. Because it changes how the agent writes code, review the code it produces as you would any other code, especially before running it or committing it.
Note that the skill's guidance mentions tools such as uv, pip-compile, pydantic, structlog and typer. Those are third-party packages that you install yourself when you follow the advice.
- No scripts run and no network use is declared
- Review generated code before running or committing it
- Packages the guidance mentions must be installed by you
What tips help you get better results?
State your Python version and style rules at the start of a request. Ask for a review before optimization, and ask for profiling data before changes to performance-sensitive code. For packaging, name the tool you use, such as uv or pip-compile, so the agent matches your workflow.
For async work, say which calls are blocking. The skill warns against blocking the event loop, and telling the agent which parts touch disk or a slow API helps it choose asyncio.to_thread() or run_in_executor().
- Name your Python version and any style rules in the request
- Ask for profiling with cProfile before optimizing
- Specify uv or pip-compile for dependencies
- Flag blocking calls in async code so they can be moved off the event loop
What people use it for
- Writing a typed Python module with pytest tests for a team codebase
- Reviewing existing code for mutable default arguments, bare except clauses and blocking async calls
- Setting up pyproject.toml and a uv or pip-compile dependency workflow for a new project
- Learning idiomatic Python, such as dataclasses versus pydantic models or when to use asyncio.gather()
- Investigating performance by profiling with cProfile before changing code
Frequently asked questions
How do I install the python-expert skill?
Download the ZIP from this page and unzip it into ~/.claude/skills/ for personal use, or into a project's .claude/skills/ folder. In the Claude apps, you can instead upload it under Settings → Capabilities → Skills.
Does the python-expert skill need anything else installed?
The source lists no required tools and declares no scripts or network use. The guidance assumes Python 3.10 or later and PEP 8, and you need your own Python environment to run the code.
Is the python-expert skill free to use?
The skill is licensed under Apache-2.0, as stated on this page. Check the license file in the repository for the full terms.
Does the skill run code or install packages for me?
No. The skill runs no scripts, makes no network calls and adds no tools. It only gives the agent written guidance on conventions.
What is the python-expert skill not good for?
It does not build finished applications or run software by itself. Projects on Python versions earlier than 3.10, or with different style standards, may get suggestions that do not fit.
How is this different from just asking an agent for Python code?
The skill gives the agent a fixed set of conventions to follow, such as type annotations, pytest tests, pyproject.toml packaging and avoiding specific pitfalls. Without it, the agent uses its default style, which may vary from request to request.
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Our verdict
Use the python-expert skill if you want Python code written or reviewed to modern conventions, or if you are learning idiomatic Python, async patterns or project structure. It is guidance only, so you still need your own environment to run and test the results. If you need a finished application, or your project uses Python older than 3.10 or a different style standard, choose something else.
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