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improve-codebase-architecture

Identify shallow, tightly coupled modules and propose deepening refactors.

Updated May 9, 2026
Search Tags:#refactoring#software design#testability#maintainability#codebase architecture#module deepening#AI navigability
One-click install
npx skills add https://github.com/kk20300113-png/my-claude-skills --skill improve-codebase-architecture-kk20300113-png
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: improve-codebase-architecture
Source: https://github.com/kk20300113-png/my-claude-skills/tree/main/improve-codebase-architecture
Command: npx skills add https://github.com/kk20300113-png/my-claude-skills --skill improve-codebase-architecture-kk20300113-png

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the friction caused by shallow, tightly coupled code modules that are hard to test, maintain, and for AI tools to navigate, by surfacing actionable refactoring opportunities to consolidate logic into deeper, more maintainable structures.

Core Features & Use Cases

  • Architecture Exploration: Organically scans codebases to identify shallow modules, tightly coupled seams, and untested areas using the deletion test to validate candidates.
  • ADR & Domain Alignment: Respects existing project architectural decision records (ADRs) and domain language from CONTEXT.md to avoid re-litigating past decisions and ensure suggestions fit the project's context.
  • Deepening Refactor Proposals: Surfaces concrete opportunities to turn shallow modules into deep ones, improving testability by making the module interface the sole test surface and concentrating change locality for maintainers.
  • Use Case: For a codebase with scattered, duplicated payment processing logic across multiple small modules, this Skill identifies the opportunity to consolidate the logic into a single deep module with a clear interface, eliminating duplicate code and simplifying test suites.

Quick Start

Use the improve-codebase-architecture skill to analyze the current project's codebase and identify the top 3 highest-impact opportunities to consolidate shallow modules into deeper, more maintainable architecture.

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 for codebase refactoring?▼

To identify shallow modules for codebase refactoring, scan your project to find tightly coupled seams and untested areas, applying the deletion test to validate shallow module candidates before consolidating them into deeper structures.

What is a deep module in software design and how does it improve maintainability?▼

In software design, a deep module is a structure that hides complex logic behind a small, high-leverage interface to improve maintainability by centralizing test surfaces and concentrating change locality for maintainers.

How do I improve AI navigability of internal code repositories?▼

Improve AI navigability of internal code by refactoring shallow, scattered modules into deeper, maintainable architecture with clear, high-leverage interfaces, eliminating duplicate code and reducing maintenance friction for automated tools.

Does this refactoring approach respect existing architectural decision records?▼

Yes, this refactoring approach respects existing architectural decision records (ADRs) and domain vocabulary from CONTEXT.md, ensuring suggestions fit the project context and avoid re-litigating past architectural decisions.

How do I consolidate duplicate payment processing logic across multiple modules?▼

Consolidate duplicate payment processing logic by identifying scattered shallow modules and merging their logic into a single deep module with a clear interface, eliminating duplicate code and simplifying test suites.

When should I not use deep module refactoring on my codebase?▼

Avoid deep module refactoring if your codebase lacks established architectural decision records or domain vocabulary, as the process relies on these to prevent re-litigating past decisions and ensure contextual architectural fit.

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