ai-literacy-assessment

Assess AI literacy by scanning repository signals like CI, harness artifacts, agents, and specification patterns, then combining that evidence with targeted clarifying questions to produce a timestamped assessment document and README badge.

A repository audit for AI collaboration maturity evaluates a team's proficiency with AI tools by analyzing static repository files and resolving gaps with guided questions to generate a defensible, dated assessment markdown file.

Generate a README badge by running an assessment that scans repository evidence, asks clarifying questions, and updates the README file with a badge reflecting the team's mapped AI literacy level.

Yes, you need both read and write access to the repository to scan files, create the assessments/YYYY-MM-DD-assessment.md document, and update README badges with the resulting literacy level.

Yes, you can automate a pre-release readiness check or quarterly review baseline by scanning repository signals and applying habitat hygiene changes like HARNESS.md and REFLECTION_LOG.md entries alongside the generated assessment.

The best way to baseline AI tool usage maturity is combining static repository signal analysis with 3-5 focused clarifying questions to resolve ambiguous gaps and produce actionable recommendations for advancing literacy levels.