audit-codebase

Name: audit-codebase
Availability: InStock
Author: Dektora

Audit Python source-code architecture for module depth and complexity.

Updated Jun 2, 2026

Search Tags:#code complexity #codebase audit #module depth #architecture quality #source-code analysis

Ready to run

npx skills add https://github.com/Dektora/dekspec-public --skill audit-codebase-dektora

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: audit-codebase
Source: https://github.com/Dektora/dekspec-public/tree/main/plugins/dekspec/skills/audit-codebase
Command: npx skills add https://github.com/Dektora/dekspec-public --skill audit-codebase-dektora

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a detailed audit of a codebase's source-code architecture quality, identifying issues such as module depth, information hiding, and code complexity, to ensure maintainability and performance.

Core Features & Use Cases

Codebase Audit: Performs a comprehensive audit of source-code architecture.
Read-Only Analysis: Classifies modules, identifies information leakage, and analyzes test-surface gaps without modifying the code.
Fix Mode: (Optional) Apply suggested fixes to flagged findings, such as restructuring deep modules.
Use Case: Ideal for engineering teams that need to ensure their codebase follows best practices in architecture and maintainability.

Quick Start

Run the audit on your codebase using the 'audit-codebase' skill and analyze the findings it generates.

Frequently Asked Questions about audit-codebase

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

FAQPage Schema

How do I audit codebase architecture quality and identify code complexity issues?▼

You can perform a read-only source-code analysis to classify modules, identify information leakage, and analyze test-surface gaps. This read-only mode evaluates your architecture's structural health and flags findings without modifying any existing code.

Can I automatically fix deep modules and information hiding issues found during an architecture review?▼

Yes, you can automatically apply suggested fixes to flagged findings by running the architecture review in fix mode. This mode restructures deep modules and addresses information leakage to actively improve your codebase's maintainability.

What is module depth and information hiding in source-code analysis?▼

Module depth and information hiding in source-code analysis refer to how much implementation detail a module conceals versus how much it exposes. Evaluating these metrics during a codebase audit helps ensure your architecture follows best practices for long-term maintainability.

Does this codebase audit tool support Python source-code analysis?▼

Yes, this codebase audit tool supports Python source-code analysis by using built-in tools to classify modules and evaluate architecture quality. It is designed for engineering teams needing to ensure their Python codebase follows strict structural best practices.

When should I run a codebase health check for architecture quality?▼

You should run a codebase health check for architecture quality when preparing for a major refactoring effort or during regular architecture reviews. This source-code analysis identifies maintainability issues like high code complexity and test-surface gaps before they impact performance.