ai-assessment-scale

Apply the 5-level AI Assessment Scale to software projects and produce a structured report.

44|2|Updated Feb 5, 2026

Search Tags:#ai #transparency #assessment #risk-management #software-development #aias

Ready to run

npx skills add https://github.com/mastepanoski/claude-skills --skill ai-assessment-scale

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-assessment-scale
Source: https://github.com/mastepanoski/claude-skills/tree/main/skills/ai-assessment-scale
Command: npx skills add https://github.com/mastepanoski/claude-skills --skill ai-assessment-scale

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Evaluators and teams need a clear, standardized way to quantify and communicate how much AI contributes to a project, ensuring transparency and governance across development stages.

Core Features & Use Cases

Defines a 5-level framework to categorize AI involvement from no AI to full AI exploration.
Facilitates transparent documentation of AI usage in planning, implementation, testing, and reporting.
Useful for open-source projects, audits, and stakeholder communications to demonstrate responsible AI engagement.

Quick Start

Outline how to apply the AI Assessment Scale to a software project and document the findings.

Frequently Asked Questions about ai-assessment-scale

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

FAQPage Schema

What is the AI Assessment Scale framework for software development?▼

The AI Assessment Scale (AIAS) is a 5-level framework used to categorize and quantify AI involvement in software development, ensuring transparency and governance across planning, implementation, testing, and reporting stages.

How do I measure AI involvement in a software project?▼

To measure AI involvement, apply the 5-level AIAS framework to project planning, development, testing, and documentation, then produce a structured assessment report capturing evidence of human oversight, decision points, and transparency disclosures.

How do I document AI usage transparency for software audits?▼

Document AI usage transparency by applying the AIAS framework to capture evidence of human oversight and decision points across all development stages, generating a structured report suitable for stakeholder communications and audits.

Can I assess AI risk management across different software development stages?▼

Yes, you can assess AI risk management by applying the 5-level AIAS framework to quantify AI contributions during planning, development, testing, and documentation, justifying assigned levels with evidence of human oversight.

Does the AIAS framework support full AI exploration levels in software projects?▼

Yes, the AIAS framework defines a 5-level categorization ranging from no AI to full AI exploration, allowing teams to accurately map and document the spectrum of AI contributions within a software project.

When do I need a standardized AI transparency assessment for software development?▼

You need a standardized AI transparency assessment when evaluating open-source projects, conducting audits, or communicating with stakeholders to demonstrate responsible AI engagement and justify human oversight decisions.