Domino Skills

Domino Skills extend coding assistants with platform-specific actions. Inside a Domino workspace, your agent automatically gains access to specific skills, including running jobs, registering models, tracking experiments, deploying apps, and more.

How skills work

Skills load automatically when a coding assistant starts inside a Domino workspace. The agent detects the Domino project and loads the Domino Skills preinstalled in the Domino Standard Environment. The skills are published in the public domino-ai-plugin repository, which replaced domino-claude-plugin; the Domino skills reference covers what the plugin ships and how to install, update, or move it. You don’t need to install or configure skills manually. To use a skill, reference the skill by name when prompting your agent. For example:

Use the modeling assistant skill. Analyze the dataset in this project
and train a few models to predict diabetes.

The agent activates the skill and begins working with full access to Domino platform resources.

Available skills

The current plugin release ships the following 35 skills. From Domino 6.3.1, each time a Workspace starts, including a restart, Domino updates Claude Code’s copy to the latest release for your Domino version when the Workspace can reach GitHub. Codex and GitHub Copilot keep the copy their Workspace first launched with, which can be an earlier release with fewer skills or older names. For 6.3.0 images and the other conditions, see Preinstalled in Workspaces.

Development & modeling

Skill	Description
domino-modeling-assistant	AI-assisted model development that runs analysis and training as Domino Jobs through the bundled MCP server
domino-experiment-tracking	Track experiments in the MLflow-based Experiment Manager and register models
domino-experiment-setup	Generate MLflow experiment setup code for a Project
domino-environments	Create and customize Compute Environments with Dockerfile instructions, and troubleshoot builds
domino-workspaces	Launch and configure Workspaces, including persistence and SSH access
domino-projects	Work with Git-based and DFS Projects, Git credentials, collaborators, and settings

Jobs & orchestration

Skill	Description
domino-jobs	Run, schedule, and monitor Jobs from the UI, CLI, or REST API
domino-flows	Orchestrate multi-step pipelines with Domino Flows (Flyte)
domino-airflow-kubeflow	Start and wait for Domino Jobs from an existing Apache Airflow or Kubeflow Pipelines deployment
domino-launchers	Create parameterized web forms that run a script as a Job
domino-distributed-computing	Work with Spark, Ray, Dask, and Open MPI clusters attached to a Workspace or Job
domino-hpc-slurm	Run Slurm workloads on a cluster attached to a Workspace, and HPC Jobs over the API

Data

Skill	Description
domino-datasets	Create, mount, snapshot, and share Domino Datasets
domino-data-connectivity	Choose between Data Sources, External Data Volumes, mounted S3 buckets, and cloud credential propagation
domino-data-sdk	Use the domino-data SDK for Data Sources, Datasets, and training sets
netapp-volumes	Work with Domino Volumes for NetApp ONTAP and their snapshots
tags-and-properties	Organize entities with tags, namespaces, and typed properties through the Taxonomy API

Deployment & monitoring

Skill	Description
domino-model-endpoints	Publish, call, and debug Domino endpoints
domino-model-serving	Automate Domino endpoints and registered models over REST
domino-model-delivery	Run batch scoring Jobs and export models to a registry, NVIDIA Fleet Command, Snowflake, or SageMaker
domino-model-monitoring	Monitor deployed models with drift detection and model quality tracking
domino-apps	Publish, update, and roll back web Apps behind Domino’s reverse proxy, and automate them over the Apps API
domino-governance	Work with governance policies, bundles, evidence, findings, and approvals

GenAI & LLM

Skill	Description
domino-genai-tracing	Trace and evaluate GenAI applications and agents with the Domino SDK
domino-trace-setup	Add GenAI tracing helpers and wiring to an agent project
domino-llm-access	Choose how code reaches an LLM: LLM Gateway 2.0 where installed, a Domino-hosted model, or an external provider
domino-llm-gateway	Call models through LLM Gateway 2.0 with the OpenAI and Anthropic SDKs

Apps & APIs

Skill	Description
domino-app-init	Scaffold a Domino-ready web app with Vite+React, Streamlit, Dash, Flask, FastAPI, and other frameworks
domino-rust-apps	Build a Rust web App with `axum`, pin the Rust version in a Compute Environment, and publish a prebuilt binary that the App starts without compiling
domino-debug-proxy	Diagnose reverse-proxy and routing problems in published Apps
domino-ui-bootstrap	Bootstrap a React and TypeScript project on the Domino Design System
domino-extensions	Build and operate Domino Extensions
domino-api-intro	Authenticate and call the Domino API, including hosts, pagination, and errors
domino-python-sdk	Programmatically interact with Domino using the python-domino SDK and REST API
domino-cli	Use the Domino CLI and R package to sync Project files, run Jobs, and upload to Datasets

Use skills in practice

When you ask your coding agent to perform a Domino-specific task, the agent selects and activates the appropriate skill. For example:

“Train a model on the diabetes dataset and track the experiment” activates the domino-modeling-assistant and domino-experiment-tracking skills.
“Deploy this model as an API endpoint” activates the domino-model-endpoints skill.
“Create a Streamlit app for this project” activates the domino-app-init skill.
“Set up a Spark cluster and run this distributed job” activates the domino-distributed-computing skill.

Modeling assistant walkthrough has a complete example of the modeling assistant skill in action.

Next steps

Get started: Launch a workspace and authenticate your coding agent.
Domino skills reference: What the plugin ships, and how to install, update, or move it.
Modeling assistant walkthrough: An end-to-end demo of data analysis, model training, and comparison using skills.

Core Concepts

Features

How skills work

Available skills

Development & modeling

Jobs & orchestration

Data

Deployment & monitoring

GenAI & LLM

Apps & APIs

Use skills in practice

Next steps

​How skills work

​Available skills

​Development & modeling

​Jobs & orchestration

​Data

​Deployment & monitoring

​GenAI & LLM

​Apps & APIs

​Use skills in practice

​Next steps

How skills work

Available skills

Development & modeling

Jobs & orchestration

Data

Deployment & monitoring

GenAI & LLM

Apps & APIs

Use skills in practice

Next steps