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Found 121 Skills
Modern Python tooling best practices using uv, ruff, ty, and pytest. Mandates the Trail of Bits Python coding standards for project setup, dependency management, linting, type checking, and testing. Based on patterns from trailofbits/cookiecutter-python.
Develop Python applications using modern patterns, uv, functional-first design, and production-first practices. Use this whenever working with .py files, pyproject.toml, uv commands, pip/pip3, poetry, virtualenv/venv, inline script metadata, or Python tooling like pytest, mypy, ruff, asyncio, itertools, functools, or dataclasses. If the task involves running Python, managing Python dependencies, creating environments, or building Python packages, load this skill and prefer uv-oriented workflows.
Dev environment setup for Megatron Bridge — container-based development, uv package management, lockfile regeneration, adding dependencies, Slurm container usage, and common build pitfalls.
Configure Python package metadata, setup.py, and pyproject.toml for distribution using UV or setuptools. Use when setting up Python packages, configuring build systems, or preparing projects for PyPI publication.
Python project scaffolding and development with modern tooling. Use when creating new Python projects, setting up virtual environments, configuring dependencies, or working with Flask web applications. Triggers on mentions of Python setup, uv, Flask, pytest, or project initialization.
Fast Python environment management with uv (10-100x faster than pip). Triggers on: uv, venv, pip, pyproject, python environment, install package, dependencies.
Use this skill for data pipeline work — ingestion with dlt, transformations with sqlmesh, analytics with DuckDB/MotherDuck, DataFrames with polars, notebooks with marimo, and project management with uv.
Creates a new Mojo or MAX project. Use when wanting to start a new Mojo or MAX project, initializing the Pixi or UV environment to use Mojo or MAX, or when the user wants to begin a new Mojo or MAX project from scratch.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
Build Docker images for Python services following team conventions. Use this skill when writing Dockerfiles, authoring CI image build pipelines, or adding a new service — covers mitodl image naming, git short-ref tags, relocatable uv venvs, and shared library handling.
For the creation, review, refactoring, and presentation of .ipynb Notebooks (Jupyter / JupyterLab / Google Colab / VS Code). Covers engineered directory structures, efficient token processing, demonstration/sharing patterns, and reproducible workflows with uv/venv.
Use this skill when the user wants to manage Python projects, virtual environments, or dependencies using uv, including creating venvs, installing packages, syncing environments, or running Python tools.