Agent Assist skill¶

The Agent Assist skill (datarobot-agent-assist) packages the same agent design, coding, and deployment workflows as the dr assist terminal assistant for use inside third-party coding agents. Instead of running Agent Assist in a dedicated terminal session, you install the skill into your preferred agent to drive the workflow through natural language in that environment.

The skill can be found in the DataRobot Agentic Skills repository alongside other DataRobot skills. It guides you through designing an agent, scaffolding from the Agentic Starter application template, implementing tools and code, and deploying to DataRobot.

Install the skill¶

Install all DataRobot skills (including Agent Assist and the required datarobot-setup skill) with the universal skills installer:

npx ai-agent-skills install datarobot-oss/datarobot-agent-skills

By default, the installer copies skills to all supported coding agents on your machine. To target a specific agent, add the --agent flag:

npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent cursor
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent claude

You can also install from agent-specific marketplaces or extension catalogs:

For agent-specific installation details and the full list of supported agents, see DataRobot agentic skills.

Verify installation¶

After installing, ask your coding agent What DataRobot skills do I have available?.

You should see datarobot-setup and datarobot-agent-assist listed. The skill source and helper scripts are in skills/datarobot-agent-assist/ in the repository.

Configure your environment¶

Before designing or coding an agent, run the datarobot-setup skill once per workspace. It checks Python and other dependencies, configures your DataRobot API token, and prepares a project directory.

There are two ways to trigger setup:

• Type: Run datarobot-setup
• Or use the slash command: ./datarobot-setup

Accept the prompts to complete environment configuration. If setup runs again in a later session, allow it to ensure the prerequisites are current.

Use Agent Assist in your coding agent¶

Start the Agent Assist workflow with either:

• Run datarobot-agent-assist
• ./datarobot-agent-assist

The skill presents the same three options as dr assist:

1. Design an AI agent: Clarify requirements and produce agent_spec.md.
2. Code an AI agent: Scaffold from the agent template and implement the spec.
3. Deploy an AI agent: Deploy the implemented agent to DataRobot.

Typical workflow¶

The following sequence takes you from idea to deployed agent in one session:

1. Design: Describe what you want to build in plain language. Agent Assist asks clarifying questions and writes an agent_spec.md blueprint before any code is written.
2. Rehearse (optional): Run a dress-rehearsal simulation to chat with your agent concept as an end user. When satisfied, type Done to move to coding.

3. Test locally: Say Let's code it. The skill handles dependencies, tools, and project structure. Watch for Lint clean and Tests passed in the output. Run the agent locally with:

   dr run dev
   

   Open the localhost URL shown in the terminal to verify the agent is running.

4. Deploy: Enter Deploy my agent to publish it to DataRobot. Deployment typically takes 10 to 30 minutes; keep the session open while it runs. Ask What's the URL for my deployed agent? to retrieve the live URL.

For field definitions and examples of agent_spec.md, see Agent specification reference. For environment variables and configuration used during coding and deployment, see Environment and commands reference.

Agent Assist skill vs. dr assist¶

Both paths use the same agent_spec.md format, agent template, and deployment model. Choose the implementation that fits your workflow.