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digital-twin-universe Skill

AI Agent SkillPythonOpen source

Use when the user needs an isolated, realistic deployment environment to test code beyond "tests pass on my machine." Covers launching environments from declarative profiles, executing commands inside them, managing their lifecycle, debugging networking or provisioning issues, and working with Incus containers. Also us Published by microsoft in amplifier-bundle-digital-twin-universe.

What is digital-twin-universe Skill?

Use when the user needs an isolated, realistic deployment environment to test code beyond "tests pass on my machine." Covers launching environments from declarative profiles, executing commands inside them, managing their lifecycle, debugging networking or provisioning issues, and working with Incus containers. Also us Published by microsoft in amplifier-bundle-digital-twin-universe. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
21/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Testing
  • Deployment
  • Documentation
  • Testing use cases
  • Deployment use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use digital-twin-universe Skill

  • Use it for testing.
  • Use it for deployment.
  • Use it for documentation.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/amplifier-bundle-digital-twin-universe
  • Skill file: skills/digital-twin-universe/SKILL.md

What it does

Use when the user needs an isolated, realistic deployment environment to test code beyond "tests pass on my machine." Covers launching environments from declarative profiles, executing commands inside them, managing their lifecycle, debugging networking or provisioning issues, and working with Incus containers. Also us

Skill instructions

Digital Twin Universe Environments amplifier-digital-twin is a CLI for on-demand, isolated environments launched from declarative profiles. Environments can be updated in-place (pull fresh code, reinstall) without destroying and relaunching. All commands output JSON to stdout. Prerequisites Check Before any DTU operation, verify the environment: bash 1. Double check the CLI is installed which amplifier-digital-twin 2. Is Incus available and running? which incus && incus version && echo "Incus OK" || echo "Incus NOT available" If amplifier-digital-twin is not found: bash uv tool install git+https://github.com/microsoft/amplifier-bundle-digital-twin-universe@main Installing Incus If the user doesn't have Incus installed, walk them through the platform-specific steps in the install guide. Present sudo commands to the user one at a time. If their system is not in the documentation, go to the actual documentation at https://linuxcontainers.org/incus/docs/main/installing/ readfile("@digital-

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Frequently asked questions

What is digital-twin-universe?

digital-twin-universe is a open-source AI agent skill with Copy skill directory. Use when the user needs an isolated, realistic deployment environment to test code beyond "tests pass on my machine." Covers launching environments from declarative profiles, executing commands.

Who is digital-twin-universe best for?

digital-twin-universe is best for reusing agent instructions, scripts, and references, testing workflows, deployment workflows, documentation workflows.

How do I install digital-twin-universe?

Install or run digital-twin-universe using Copy skill directory. Check digital-twin-universe for the latest setup command.

Is digital-twin-universe actively maintained?

digital-twin-universe may need a closer maintenance check before production use.

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Stars
6
Forks
3
Last commit
1 month ago
Repository age
4 months
License
MIT

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