improve-codebase-architecture

Analyze codebases to identify architectural friction and propose RFC-style design options.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/fuxiang123/unity-harness --skill improve-codebase-architecture-fuxiang123
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: improve-codebase-architecture
Source: https://github.com/fuxiang123/unity-harness/tree/main/assets/github/skills/improve-codebase-architecture
Command: npx skills add https://github.com/fuxiang123/unity-harness --skill improve-codebase-architecture-fuxiang123

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Surface architectural friction in a codebase and surface opportunities to deepen shallow modules to improve testability and AI-navigability.

Core Features & Use Cases

  • Identify module boundaries and coupling points to reveal design friction.
  • Propose architecture refactors and RFC-style proposals to deepen modules.
  • Generate user-facing guidance for AI-assisted codebase improvements (RFC templates, task breakdowns).

Quick Start

Begin by scanning the repository to surface deepening opportunities and generate RFC-style design proposals.

Frequently Asked Questions about improve-codebase-architecture

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify shallow modules in my codebase to improve testability?

To improve testability, you can scan your repository to surface architectural friction and identify module boundaries where deepening opportunities exist for better separation of concerns.

What is the best way to refactor architectural boundaries in a large multi-module project?

Refactoring architectural boundaries in large projects benefits from generating RFC-style design proposals that frame the problem space and compare multiple interface options to guide structural improvements.

Can I generate RFC proposals for codebase refactoring using an automated approach?

Yes, you can produce RFC-style candidates by exploring your codebase to surface design friction, generating proposals that include task breakdowns and interface comparisons for AI-assisted improvements.

Does this approach work for improving AI-navigability in existing codebases?

Yes, improving AI-navigability is a core outcome of deepening shallow modules, as it reduces coupling points and clarifies modular boundaries to make the codebase structure more transparent for AI tools.

When do I need architectural refactoring for testability improvements?

You need architectural refactoring when shallow modules and high coupling create design friction, making it difficult to isolate components for effective testing in large or multi-module projects.

What are the limitations of deepening modules to fix architectural friction?

Deepening modules requires careful problem-space framing and interface comparison, meaning it produces RFC-style candidates for planning rather than automatically applying code changes to your codebase.