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agent-native-audit

Audit codebases for AI agent readiness across five scored dimensions.

Updated Feb 26, 2026
Search Tags:#refactoring#codebase analysis#developer productivity#code audit#agent-native#AI readiness
One-click install
npx skills add https://github.com/designxdevelop/agent-skills --skill agent-native-audit-designxdevelop
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-native-audit
Source: https://github.com/designxdevelop/agent-skills/tree/main/skills/agent-native-audit
Command: npx skills add https://github.com/designxdevelop/agent-skills --skill agent-native-audit-designxdevelop

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you understand how easily AI coding agents can understand, navigate, and modify your codebase, providing a clear path to making your code more "agent-native."

Core Features & Use Cases

  • Codebase Auditing: Evaluates your project across five key dimensions: Type Safety, Traversability, Test Coverage, Feedback Loops, and Self-Documentation.
  • Scored Rubric: Provides a quantitative score (1-5) for each dimension and an overall grade.
  • Prioritized Refactoring Plan: Offers actionable steps to improve your codebase's agent-nativeness, focusing on high-impact changes.
  • Use Case: A developer wants to know if their new project is ready for AI-assisted development tools like Cursor or Claude Code. They run this audit to get a score and a plan to improve it.

Quick Start

Run an agent-native audit on the current project.

Frequently Asked Questions about agent-native-audit

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

FAQPage Schema
How do I check if my codebase is ready for AI coding agents?▼

An agent-native audit evaluates your codebase for AI agent readiness by scoring type safety, traversability, test coverage, feedback loops, and self-documentation. It provides a quantitative score from 1 to 5 for each dimension to gauge AI readiness.

What does codebase traversability mean for AI-assisted development?▼

Codebase traversability measures how easily an AI agent can navigate your project structure. The audit scores this dimension to ensure agents can effectively understand and traverse code paths during development.

How do I get a refactoring plan to improve my code for AI tools?▼

Running an agent-native audit generates an optional prioritized refactoring plan. It provides actionable steps focusing on high-impact changes to enhance your codebase's AI-assisted development capabilities.

Can I audit code structure and type system strictness for AI comprehension?▼

Yes, you can audit code structure and type system strictness to assess AI comprehension. The audit specifically evaluates whether your fully typed codebase and clear structure allow agents to understand and modify your project.

Does test suite completeness affect AI readiness scores?▼

Test suite completeness directly affects AI readiness scores because it evaluates feedback loops. High test coverage ensures AI agents receive immediate validation when modifying your codebase, improving overall agent-native capabilities.

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