plan-marshall-plugin
Python domain extension with pyprojectx build operations and workflow integration
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Python domain extension with pyprojectx build operations and workflow integration
Maintain the public Python API for eo-processor, including exports, __all__, docstrings, and type stubs. Use when adding/renaming functions, changing signatures/behavior, or ensuring Python typing and user-facing docs stay consistent with the Rust/PyO3 core.
Validate Python toolchain alignment between mise, Poetry, and pyproject. Use when changing Python versions, editing pyproject.toml, or seeing Poetry/mise version solver errors. Invokes /toolchain-health to check: - .mise.toml python tool version - pyproject.toml python constraint - Poetry env python interpreter Keywords: python version, mise, poetry, toolchain, env use, lock, install
Fast Python dependency management with uv package manager for virtual environments and project workflows. WHEN: Installing packages with uv, creating virtual environments, managing dependencies with uv.lock, setting up Python projects with uv init. WHEN NOT: Packaging libraries for distribution (use python-packaging), using pip/poetry/pipenv instead of uv.
Detects Python project configuration and provides commands for testing, building, coverage, and containerization. Use when: Starting workflow, detecting project stack, need TEST_CMD Triggers: detect stack, what commands, initial setup Outputs: TEST_CMD, BUILD_CMD, COVERAGE_CMD, COVERAGE_CHECK, MIGRATE_CMD
Bootstrap a new Python project using the OCREvaluation default layout and toolchain (uv, ruff, ty, pre-commit). Use when asked to scaffold a new Python repo, initialize standard folders, or set up uv/ruff/ty/pre-commit configs to match this repo.
Python coding standards, best practices, type hints, and testing patterns with uv for package management. Use when writing or reviewing Python code, implementing tests, setting up Python projects, managing dependencies with uv, working with virtual environments, adding type hints, writing pytest tests, or discussing Python language features and best practices.
Use when creating Python projects, managing dependencies, or running Python scripts. Covers uv package manager commands, best practices, and common patterns for modern Python development.
Setup a new python project in this directory.
UV-specific patterns for single-file Python scripts using inline metadata (PEP 723). Use when creating Python hooks, standalone utilities, or executable scripts in UV-managed projects.
Python development with uv, pytest, ruff, and type hints. Use when writing Python code, running tests, managing Python packages, or working with virtual environments. Covers import organization, type hints, pytest patterns, and environment variables.
Use when maintaining a fork of a Python package without GitHub access, importing upstream releases from PyPI tarballs, or merging upstream updates into a fork using vendor branch strategy
Detects the Python major and minor version of the current repository
Check and validate the AutoChip development environment dependencies including chip simulators (Verilator/VCS/SimVision) and Python packages (torchbit, cocotb, jsonschema) in conda environments
Apply Python tooling standards including uv package management, pytest testing, ruff/mypy code quality, one-line docstrings, and self-documenting code practices. Use this skill when working with Python backend code, managing dependencies, running tests, or ensuring code quality. Apply when installing packages, writing tests, formatting code, type checking, adding docstrings, organizing imports, or deciding whether to create new files vs. extending existing ones. Use for any Python development task requiring adherence to tooling standards and best practices.
Python development best practices for modern Python projects. Activated when working with Python files, pyproject.toml, or discussing Python patterns, testing, linting, type hints.
Fast Python package and project management using Astral's uv. Use when installing packages, managing virtual environments, running Python scripts, or initializing Python projects. Triggers on: pyproject.toml, requirements.txt, Python dependency discussions, virtual environment setup.
Automatically manage Python virtual environments (.venv) in terminal commands. Always activate .venv before running Python/pip commands. Use when executing Python scripts, installing packages, or running development servers. Critical for consistent environment management.