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Modern Python

OrganizationPopular
trailofbits
modern-python

Configures Python projects with modern tooling (uv, ruff, ty). Use when creating projects, writing standalone scripts, or migrating from pip/Poetry/mypy/black.

Overview

Publishertrailofbits
Repositoryskills
Skill namemodern-python
Stars
7.1K
Forks
611
Bundled files
13
LicenseCC-BY-SA-4.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 13 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by trailofbits on GitHub. Read the source before you install it.

Installation

Install the Modern Python AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/trailofbits/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/modern-python/skills/modern-python .claude/skills/modern-python
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Modern Python in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Modern Python on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Modern Python is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Modern Python

Guide for modern Python tooling and best practices, based on trailofbits/cookiecutter-python.

When to Use This Skill

  • Creating a new Python project or package
  • Setting up pyproject.toml configuration
  • Configuring development tools (linting, formatting, testing)
  • Writing Python scripts with external dependencies
  • Migrating from legacy tools (when user requests it)

When NOT to Use This Skill

  • User wants to keep legacy tooling: Respect existing workflows if explicitly requested
  • Python < 3.11 required: These tools target modern Python
  • Non-Python projects: Mixed codebases where Python isn't primary

Anti-Patterns to Avoid

AvoidUse Instead
[tool.ty] python-version[tool.ty.environment] python-version
uv pip installuv add and uv sync
Editing pyproject.toml manually to add depsuv add <pkg> / uv remove <pkg>
hatchling build backenduv_build (simpler, sufficient for most cases)
Poetryuv (faster, simpler, better ecosystem integration)
requirements.txtPEP 723 for scripts, pyproject.toml for projects
mypy / pyrightty (faster, from Astral team)
[project.optional-dependencies] for dev tools[dependency-groups] (PEP 735)
Manual virtualenv activation (source .venv/bin/activate)uv run <cmd>
pre-commitprek (faster, no Python runtime needed)

Key principles:

  • Always use uv add and uv remove to manage dependencies
  • Never manually activate or manage virtual environments—use uv run for all commands
  • Use [dependency-groups] for dev/test/docs dependencies, not [project.optional-dependencies]

Decision Tree

What are you doing?
├─ Single-file script with dependencies?
│   └─ Use PEP 723 inline metadata (./references/pep723-scripts.md)
├─ New multi-file project (not distributed)?
│   └─ Minimal uv setup (see Quick Start below)
├─ New reusable package/library?
│   └─ Full project setup (see Full Setup below)
└─ Migrating existing project?
    └─ See Migration Guide below

Tool Overview

ToolPurposeReplaces
uvPackage/dependency managementpip, virtualenv, pip-tools, pipx, pyenv
ruffLinting AND formattingflake8, black, isort, pyupgrade, pydocstyle
tyType checkingmypy, pyright (faster alternative)
pytestTesting with coverageunittest
prekPre-commit hooks (setup)pre-commit (faster, Rust-native)

Security Tools

ToolPurposeWhen It Runs
shellcheckShell script lintingpre-commit
detect-secretsSecret detectionpre-commit
actionlintWorkflow syntax validationpre-commit, CI
zizmorWorkflow security auditpre-commit, CI
pip-auditDependency vulnerability scanningCI, manual
DependabotAutomated dependency updatesscheduled

See security-setup.md for configuration and usage.

Quick Start: Minimal Project

For simple multi-file projects not intended for distribution:

bash
# Create project with uv
uv init myproject
cd myproject

# Add dependencies
uv add requests rich

# Add dev dependencies
uv add --group dev pytest ruff ty

# Run code
uv run python src/myproject/main.py

# Run tools
uv run pytest
uv run ruff check .

Full Project Setup

If starting from scratch, ask the user if they prefer to use the Trail of Bits cookiecutter template to bootstrap a complete project with already preconfigured tooling.

bash
uvx cookiecutter gh:trailofbits/cookiecutter-python

1. Create Project Structure

bash
uv init --package myproject
cd myproject

This creates:

myproject/
├── pyproject.toml
├── README.md
├── src/
│   └── myproject/
│       └── __init__.py
└── .python-version

2. Configure pyproject.toml

See pyproject.md for complete configuration reference.

Key sections:

toml
[project]
name = "myproject"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = []

[dependency-groups]
dev = [{include-group = "lint"}, {include-group = "test"}, {include-group = "audit"}]
lint = ["ruff", "ty"]
test = ["pytest", "pytest-cov"]
audit = ["pip-audit"]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["ALL"]
ignore = ["D", "COM812", "ISC001"]

[tool.pytest]
addopts = ["--cov=myproject", "--cov-fail-under=80"]

[tool.ty.terminal]
error-on-warning = true

[tool.ty.environment]
python-version = "3.11"

[tool.ty.rules]
# Strict from day 1 for new projects
possibly-unresolved-reference = "error"
unused-ignore-comment = "warn"

3. Install Dependencies

bash
# Install all dependency groups
uv sync --all-groups

# Or install specific groups
uv sync --group dev

4. Add Makefile

makefile
.PHONY: dev lint format test build

dev:
	uv sync --all-groups

lint:
	uv run ruff format --check && uv run ruff check && uv run ty check src/

format:
	uv run ruff format .

test:
	uv run pytest

build:
	uv build

Migration Guide

When a user requests migration from legacy tooling:

From requirements.txt + pip

First, determine the nature of the code:

For standalone scripts: Convert to PEP 723 inline metadata (see pep723-scripts.md)

For projects:

bash
# Initialize uv in existing project
uv init --bare

# Add dependencies using uv (not by editing pyproject.toml)
uv add requests rich  # add each package

# Or import from requirements.txt (review each package before adding)
# Note: Complex version specifiers may need manual handling
grep -v '^#' requirements.txt | grep -v '^-' | grep -v '^\s*$' | while read -r pkg; do
    uv add "$pkg" || echo "Failed to add: $pkg"
done

uv sync

Then:

  1. Delete requirements.txt, requirements-dev.txt
  2. Delete virtual environment (venv/, .venv/)
  3. Add uv.lock to version control

From setup.py / setup.cfg

  1. Run uv init --bare to create pyproject.toml
  2. Use uv add to add each dependency from install_requires
  3. Use uv add --group dev for dev dependencies
  4. Copy non-dependency metadata (name, version, description, etc.) to [project]
  5. Delete setup.py, setup.cfg, MANIFEST.in

From flake8 + black + isort

  1. Remove flake8, black, isort via uv remove
  2. Delete .flake8, pyproject.toml [tool.black], [tool.isort] configs
  3. Add ruff: uv add --group dev ruff
  4. Add ruff configuration (see ruff-config.md)
  5. Run uv run ruff check --fix . to apply fixes
  6. Run uv run ruff format . to format

From mypy / pyright

  1. Remove mypy/pyright via uv remove
  2. Delete mypy.ini, pyrightconfig.json, or [tool.mypy]/[tool.pyright] sections
  3. Add ty: uv add --group dev ty
  4. Run uv run ty check src/

Quick Reference: uv Commands

CommandDescription
uv initCreate new project
uv init --packageCreate distributable package
uv add <pkg>Add dependency
uv add --group dev <pkg>Add to dependency group
uv remove <pkg>Remove dependency
uv syncInstall dependencies
uv sync --all-groupsInstall all dependency groups
uv run <cmd>Run command in venv
uv run --with <pkg> <cmd>Run with temporary dependency
uv buildBuild package
uv publishPublish to PyPI

Ad-hoc Dependencies with --with

Use uv run --with for one-off commands that need packages not in your project:

bash
# Run Python with a temporary package
uv run --with requests python -c "import requests; print(requests.get('https://httpbin.org/ip').json())"

# Run a module with temporary deps
uv run --with rich python -m rich.progress

# Multiple packages
uv run --with requests --with rich python script.py

# Combine with project deps (adds to existing venv)
uv run --with httpx pytest  # project deps + httpx

When to use --with vs uv add:

  • uv add: Package is a project dependency (goes in pyproject.toml/uv.lock)
  • --with: One-off usage, testing, or scripts outside a project context

See uv-commands.md for complete reference.

Quick Reference: Dependency Groups

toml
[dependency-groups]
dev = ["ruff", "ty"]
test = ["pytest", "pytest-cov", "hypothesis"]
docs = ["sphinx", "myst-parser"]

Install with: uv sync --group dev --group test

Best Practices Checklist

  • Use src/ layout for packages
  • Set requires-python = ">=3.11"
  • Configure ruff with select = ["ALL"] and explicit ignores
  • Use ty for type checking
  • Enforce test coverage minimum (80%+)
  • Use dependency groups instead of extras for dev tools
  • Add uv.lock to version control
  • Use PEP 723 for standalone scripts

Read Next

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Modern Python AI skill do?

Configures Python projects with modern tooling (uv, ruff, ty). Use when creating projects, writing standalone scripts, or migrating from pip/Poetry/mypy/black.

Why use Modern Python on TypingMind?

Because you install it once and use it with any model. Modern Python is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Modern Python in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/trailofbits/skills/tree/main/plugins/modern-python/skills/modern-python. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Modern Python?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Modern Python?

As many as you like. As long as a model supports skills, you can use Modern Python with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Modern Python AI skill free?

Yes. It is published on GitHub by trailofbits under the CC-BY-SA-4.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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