What is the recommended test coverage for this skill?

The skill targets 80%+ coverage across all layers, with a specific focus on domain invariants in the models and orchestration logic in the service layer.

Does this skill work with any Python framework?

Yes, it is framework-agnostic. It emphasizes separating domain logic from frameworks like Django or FastAPI, which are treated as entrypoints or adapters.

How does it enforce architectural boundaries?

It recommends using tools like ImportLinter within the CI/CD pipeline to ensure high-level policy code never depends on low-level implementation details.

What is the difference between Cosmic Python and System Architecture?

Cosmic Python focuses on the internal code structure (how files and classes interact), while System Architecture deals with external service boundaries and deployment topology.

Cosmic Python & Clean Architecture

Name: Cosmic Python & Clean Architecture
Author: meaningfy-ws

bymeaningfy-ws

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API開発

Implements Clean Architecture and SOLID principles in Python projects through layered design and rigorous testing strategies.

概要

Cosmic Python is a specialized skill designed to help developers structure Python services using Clean Architecture principles to ensure long-term maintainability and testability. It focuses on the internal code organization—separating domain models, infrastructure adapters, orchestration services, and entrypoints—rather than external system topology. By enforcing strict dependency directions and high test coverage, this skill guides Claude in building production-grade Python systems that are easy to refactor, well-documented, and resistant to architectural drift.

主な機能

SOLID principle implementation and Clean Code standards
1 GitHub stars
Strict dependency direction validation using ImportLinter
Comprehensive testing strategies including TDD and BDD with Gherkin
Layered architectural enforcement (Models, Adapters, Services, Entrypoints)
Observability integration using structured logging and OpenTelemetry patterns

ユースケース

Refactoring legacy Python code to separate business logic from infrastructure
Bootstrapping a new Python microservice with a maintainable, testable structure
Enforcing architectural boundaries and preventing circular dependencies in team projects

概要

主な機能

SOLID principle implementation and Clean Code standards
1 GitHub stars
Strict dependency direction validation using ImportLinter
Comprehensive testing strategies including TDD and BDD with Gherkin
Layered architectural enforcement (Models, Adapters, Services, Entrypoints)
Observability integration using structured logging and OpenTelemetry patterns

ユースケース

Refactoring legacy Python code to separate business logic from infrastructure
Bootstrapping a new Python microservice with a maintainable, testable structure
Enforcing architectural boundaries and preventing circular dependencies in team projects