Does it support specific architectural patterns like Clean Architecture?

It supports patterns like Clean and Hexagonal Architecture but ensures they are applied only when the project's complexity justifies the added ceremony.

Can this skill help with existing legacy codebases?

Yes, it can analyze existing structures to identify circular dependencies and suggest how to extract modules into clear, deletable components.

How does this skill help avoid over-engineering?

It enforces a 'YAGNI' philosophy, prompting for measured evidence before adding complex patterns like microservices, event sourcing, or excessive abstraction layers.

What does 'designing for operations' mean in this context?

It focuses on making the system debuggable at 3 AM by ensuring every request is traceable, data flow is obvious, and errors include full context for reproduction.

System Architecture

Name: System Architecture
Author: bengous

bybengous

•

API Development

Designs pragmatic software architectures with appropriate complexity to match real-world scale and team constraints.

About

The System Architecture skill empowers Claude to act as a pragmatic lead architect, focusing on creating systems that are right-sized for current needs rather than imagined future ones. It guides the creation of clear domain boundaries, explicit data flows, and observable structures while aggressively avoiding premature abstractions like microservices for small teams or unnecessary repository layers. By emphasizing trade-offs and operational simplicity, it ensures that your application remains easy to understand, modify, and debug throughout its entire lifecycle.

Key Features

2 GitHub stars
Anti-pattern detection to prevent over-engineering and 'abstraction theater'
Dependency direction enforcement from infrastructure to core domain
Failure-aware design with explicit error handling and compensation
Pragmatic boundary definition between separate business domains
Built-in observability through correlation IDs and request tracing

Use Cases

Deciding when to transition from a monolith to distributed services
Designing the initial structural foundation for a new application or MVP
Refactoring legacy codebases into clear, decoupled bounded contexts

About

Key Features

2 GitHub stars
Anti-pattern detection to prevent over-engineering and 'abstraction theater'
Dependency direction enforcement from infrastructure to core domain
Failure-aware design with explicit error handling and compensation
Pragmatic boundary definition between separate business domains
Built-in observability through correlation IDs and request tracing

Use Cases

Deciding when to transition from a monolith to distributed services
Designing the initial structural foundation for a new application or MVP
Refactoring legacy codebases into clear, decoupled bounded contexts