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How to certify a model and submit it to the public registry with AI Charter

Fill in the certify form, save the JSON file, and open a pull request to list the model in the registry.

Who it is forA company compliance or AI team that wants to disclose a model's training sources, hazards, and known problems against the charter.

The problemDisclosing a model's details to the public in a consistent format is hard without a shared template and a review process.

The outcomeA certification JSON file is added to the registry through a pull request that others can review before it goes live.

What you need first

  • Node.js and npm to run the site locally
  • Git and a GitHub account to submit a pull request
  • Model details ready for the certify form: company, version, status, training sources, hazard categories, and unintended consequences

Steps

  1. Clone the repository with git and open the project folder. (inferred, check the README)
  2. Run npm install in the project folder.
  3. Run npm run dev and open the local address it prints, then go to /certify.
  4. Fill in the form for company, version, status, training sources, agentic decision-making, hazard categories, and unintended consequences, then download the certification JSON file.
  5. Add the file to src/data/certifications/ and open a pull request.

Prompt for your agent

Work in the mrtinkz/ai-charter repository. Use the certify form at /certify to create a certification JSON file for <model name>, then copy it into src/data/certifications/ and run `npm run build`. Expected output: a new JSON file in that folder and a passing build. Verify the file appears in the /registry page after `npm run dev`.

Caveat. The README says anyone can review a pull request before it goes live, but it does not describe how review decisions are made.

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