Get the FREE Ultimate OpenClaw Setup Guide →

gaelic-ghost/python-skills Skills

(4)

Browse AI agent skills from gaelic-ghost/python-skills for Claude Code, OpenClaw, Cursor, Windsurf, and more. Install them with a single command to extend what your agents can do.

bootstrap-python-mcp-service

gaelic-ghost/python-skills

1

Bootstrap Python MCP server projects and workspaces on macOS using uv and FastMCP with consistent defaults. Use when creating a new MCP server from scratch, scaffolding a single uv MCP project, scaffolding a uv workspace with package/service members, customizing scaffold defaults through layered YAML profiles, initializing pytest+ruff+mypy defaults, creating README.md, initializing git, running initial validation checks, or starting from OpenAPI/FastAPI with MCP mapping guidance.

bootstrap-python-service

gaelic-ghost/python-skills

1

Bootstrap Python FastAPI services on macOS using uv with consistent project and workspace scaffolds. Use when creating a new backend/API service from scratch, scaffolding a single uv service project, scaffolding a uv workspace with package/service members, customizing scaffold defaults through layered YAML profiles, initializing pytest+ruff+mypy defaults, creating README.md, initializing git, and running initial validation commands.

bootstrap-uv-python-workspace

gaelic-ghost/python-skills

1

Bootstrap new Python projects and multi-package workspaces with uv on macOS using deterministic scripts and consistent defaults. Use when creating a new uv Python project, scaffolding a uv monorepo/workspace, setting up package or service profiles, customizing scaffold defaults through layered YAML profiles, initializing dev tooling (pytest, ruff, mypy), creating README scaffolds, or initializing git with an optional first commit.

uv-pytest-unit-testing

gaelic-ghost/python-skills

1

Set up and run unit tests for Python uv projects and uv workspaces with pytest. Use when creating or updating pytest configuration in pyproject.toml, installing pytest dev dependencies with uv, running tests in a workspace member package via `uv run --package`, customizing pytest workflow defaults through layered YAML profiles, organizing tests with fixtures/markers/parametrize, or troubleshooting test discovery and import failures.

Sponsor this space

Reach thousands of developers