setup-skill

Python project setup creates a src-based layout with organized subdirectories for models, database, services, UI, and utilities, plus tests, configuration files, and documentation. This standardized structure ensures consistency across development workflows and makes projects scalable from the start.

A properly configured Python project includes pyproject.toml for dependencies and metadata, .gitignore to exclude unnecessary files, a README with installation and usage instructions, and __init__.py files to define package boundaries. These essentials establish a foundation for collaboration and deployment.

Yes, project scaffolding generates a complete src layout with package substructures suitable for CLI applications. You get a pre-organized structure with models, services, and utilities already in place, letting you focus on business logic instead of folder organization.

The src layout separates your package code from tests, configuration, and metadata files, reducing import conflicts and making the project structure clearer. This best-practice approach scales better and aligns with how most modern Python projects are organized.

Initialization generates a complete project skeleton with a src directory, package submodules, a tests directory, pyproject.toml, .gitignore, README with setup instructions, and __init__.py and main.py entry points, providing everything needed to start development immediately.