domino-environments

Create and customize Domino Compute Environments with Dockerfile configuration and package management.

6|3|Updated Feb 19, 2026

Search Tags:#package management #dependencies #docker #environments #compute #domino

Ready to run

npx skills add https://github.com/dominodatalab/domino-claude-plugin --skill domino-environments-dominodatalab

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: domino-environments
Source: https://github.com/dominodatalab/domino-claude-plugin/tree/main/skills/environments
Command: npx skills add https://github.com/dominodatalab/domino-claude-plugin --skill domino-environments-dominodatalab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies the creation, customization, and management of Domino Compute Environments, ensuring your development and execution environments are correctly configured with the necessary tools and packages.

Core Features & Use Cases

Environment Creation & Customization: Define and build Docker-based environments tailored to your project needs.
Package Management: Install Python, R, and system packages via Dockerfile, requirements.txt, or pre/post-run scripts.
Troubleshooting: Diagnose and resolve common environment build failures and package installation issues.
Use Case: You need to set up a new project that requires specific versions of TensorFlow and PyTorch with CUDA support. This Skill guides you through creating a custom Docker environment to meet these exact specifications.

Quick Start

Use the domino-environments skill to create a new compute environment with pandas and scikit-learn installed.

Frequently Asked Questions about domino-environments

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

FAQPage Schema

How do I create a custom Domino Compute Environment with specific Python and R packages?▼

To create a custom Domino Compute Environment, define a Dockerfile to install Python and R packages. You can manage dependencies via requirements.txt or pre/post-run scripts to ensure your environment includes the necessary tools.

Why does my Domino environment build fail when installing system packages?▼

Domino environment build failures often occur due to missing system dependencies or incorrect Dockerfile syntax. Troubleshoot by verifying package manager commands, checking dependency conflicts, and ensuring proper system package installation in your Dockerfile.

Can I set up a Domino environment with specific versions of TensorFlow and PyTorch with CUDA support?▼

Yes, you can set up a Domino environment with specific versions of TensorFlow and PyTorch with CUDA support by creating a custom Docker environment tailored to your exact specifications using a Dockerfile.

What is the best way to ensure reproducibility for Domino workspaces and jobs?▼

The best way to ensure reproducibility for Domino workspaces and jobs is to define a Docker-based compute environment with pinned package versions and consistent dependency management via Dockerfile configuration.

How do I configure an IDE in a Domino Compute Environment?▼

To configure an IDE in a Domino Compute Environment, use the environment customization features to install and set up your preferred IDE alongside your required packages and dependencies during the Docker image build process.