Ai Assessment Scale

If you need to document how much AI actually touched your codebase, this gives you a structured way to do it. It's based on the AIAS v2 framework from education research, adapted for software projects. You get five levels from "no AI" to "experimental AI exploration," with specific indicators for each. Useful when you're writing transparency reports, creating disclosure badges, or just trying to honestly communicate to stakeholders what role Claude or Copilot played in your work. The framework won't certify quality or tell you if you're using AI "correctly," but it will help you be specific about where human judgment ended and AI generation began.

skills.sh installs: 238
GitHub stars: 69
last updated: Aug 21, 2026

View on GitHub

Install

$ npx -y skills add mastepanoski/claude-skills --skill ai-assessment-scale --agent claude-code

Installs into .claude/skills of the current project.

Files

AI Assessment Scale (AIAS)

This skill enables AI agents to evaluate the level of AI contribution in software projects using the AI Assessment Scale (AIAS) framework developed by Mike Perkins, Leon Furze, Jasper Roe, and Jason MacVaugh.

The AIAS provides a 5-level framework for understanding and documenting AI's role, from zero AI assistance to creative AI exploration. Originally designed for educational assessments, this skill adapts the framework for software development so teams can transparently communicate AI involvement in their work.

Adaptation boundary: AIAS v2 is an education framework, not a software compliance standard. Use this skill to create clear disclosure and evidence summaries, not to certify project quality or rank teams by "better" AI usage.

Use this skill to assess AI contribution levels, document AI usage for transparency, and understand where human critical thinking vs AI assistance is applied throughout your project lifecycle.