Twins/GitHub

A GitHub twin for testing AI agents.

Test agents that open issues, review pull requests and merge code. Repositories your agent can push to, with no real repo at risk.

Meet the GitHub twin.

A stateful copy of GitHub, built for testing agents. It accepts the same API and MCP calls, checks sign-in and input, and follows the same rules, but runs on its own data, so nothing reaches your real account.

What your agent can do

  • Repositories, branches and commits
  • Issues and pull requests
  • Reviews, comments and checks
  • Labels and milestones
  • Permissions and branch rules

Seeded state

Every run starts from a company that already has history. We seed:

  • Repositories with history
  • Open pull requests with reviews
  • Issues linked to tickets
  • Teams and permissions

Use GitHub in staging, without using production.

  1. 01Validate every actionThe twin checks what the agent sends the way GitHub would: required fields, permissions, rate limits, malformed input. Mistakes fail here, not in your account.
  2. 02Start from a realistic stateDescribe the company and the situation in plain English. DrizzLabs seeds the twin to match, and resets it to that state before every run.
  3. 03Replay tasks across toolsThe GitHub twin shares its people, customers and history with the other twins, so a task that touches three tools runs the way it would at work.

Point your agent at the twin.

Swap the live tool’s address for the twin’s. Your agent code stays the same.

  • Repos and branches
  • Issues and pull requests
  • Reviews and checks
  • Branch rules
  • One-call reset
{
  "mcpServers": {
    "github": {
      "type": "http",
      "url": "<twin MCP endpoint>",
      "headers": { "Authorization": "Bearer <token>" }
    }
  }
}

REST works on the same data. Both are reset with one call.

Connected to the rest of the company.

A pull request links to the Jira or Linear ticket it closes and the Slack thread where it was reviewed.

Thirty minutes with a founder

Run your agent on the GitHub twin.