What problem does it solve? Python codebases often grow into tangled collections of files with unclear boundaries, hidden dependencies, and inconsistent organization. This Skill provides concrete patterns for structuring projects so modules stay cohesive, public interfaces are explicit, and directory layouts remain navigable as the codebase scales. ## Core Features & Use Cases - Module Architecture Patterns: Apply one-concept-per-file organization, explicit __all__ public API definitions, and flat directory structures that avoid deep nesting. - Layout Strategies: Choose between layered architecture, domain-driven structure, colocated tests, or parallel test directories based on project needs. - Naming and Import Conventions: Enforce snake_case file naming, absolute imports, and consistent class-to-file name matching. - Use Case: When starting a new Python library, use this Skill to design the package layout with a clean __init__.py public interface, organized service and model modules, and a parallel tests directory. ## Quick Start Ask the AI to design a directory structure and module organization plan for your new Python project, including public API definitions with all.
