acmm-audit

Community

Score and improve AI codebase maturity

Authormattbutlerengineering
Version1.0.0
Installs0

System Documentation

What problem does it solve?

It helps teams measure how AI-operable their repository is using the AI Codebase Maturity Model (ACMM), turning scattered readiness signals into an actionable maturity report.

Core Features & Use Cases

  • Canonical ACMM scoring: Evaluates project meta-properties across a 6-level rubric (L1 assisted through L6 fully autonomous) using a ported 100+ criterion catalog.
  • Actionable next-level gaps: Optionally creates deduplicated GitHub issues for criteria that block advancement.
  • Progress visibility: Writes generated state and a human-readable report under .claude/acmm/, and can rewrite the README badge for quick scanning.
  • Use case: Run an ACMM audit before scaling AI automation initiatives, then create issues targeting the next maturity step rather than relying on ad hoc review.

Quick Start

Ask the AI to run /acmm-audit with the apply flag to generate the ACMM report and open GitHub issues for the next-level gaps.

Dependency Matrix

Required Modules

None required

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: acmm-audit
Download link: https://github.com/mattbutlerengineering/mattbutlerengineering/archive/main.zip#acmm-audit

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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