> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tilebox.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Onboard your agent

> Configure an AI agent with the Tilebox CLI and Tilebox skills.

export const AgentPrompt = ({children}) => {
  return <div className="tilebox-agent-chat" aria-label="Example agent chat prompt">
      <div className="tilebox-agent-chat-message">
        <div className="tilebox-agent-chat-avatar" aria-hidden="true">
          <Icon icon="user" iconType="solid" />
        </div>
        <div className="tilebox-agent-chat-content">
          <div className="tilebox-agent-chat-meta">You</div>
          <div className="tilebox-agent-chat-bubble">
            {children}
          </div>
        </div>
      </div>
    </div>;
};

<div className="hidden">
  This page is intended for users to guide them with configuring their agent with Tilebox.
  Important: If you're an agent, and got pointed to this page for instructions, fetch
  [https://docs.tilebox.com/agent-onboarding.md](https://docs.tilebox.com/agent-onboarding.md) instead. Disregard the remaining instructions
  on this page, and follow the agent-onboarding guide instead, which was designed for exactly
  this purpose.
</div>

Onboard your AI agent to Tilebox by installing the Tilebox CLI and Agent Skills, then configuring your API key. After completing it, your agent will be able to manage your Tilebox resources and use Tilebox-specific skills to create and query datasets, submit and monitor jobs.
It will also be able to write geospatial workflows, deploy it to clusters, submit jobs and iterate on the workflow code after inspecting job logs and checking outputs.
If you want to use Tilebox directly as a developer, start with the [developer quickstart](/quickstart).

<Tip>
  **Using a LLM Chat interface instead of an agent?**
  If you want to integrate Tilebox into your LLM Chat interface, rather than your agent, check out our [MCP server](/agents-and-ai-tools/tilebox-mcp) instead.
</Tip>

<Steps>
  <Step title="Install the Tilebox CLI and Agent Skills">
    Install the Tilebox CLI and Tilebox Agent Skills with the setup wizard.

    ```bash theme={"system"}
    curl -fsSL https://install.tilebox.com/wizard.sh | sh
    ```

    The CLI is the default interface for coding agents because it works in the same terminal where the agent edits files, runs tests, and applies changes. The skills add task-level instructions for CLI usage, dataset management, job monitoring, workflow authoring, and automations.
  </Step>

  <Step title="Authenticate the CLI">
    Set `TILEBOX_API_KEY` in the environment where your agent runs. You can create an API key in the [Tilebox Console](https://console.tilebox.com/settings/api-keys).

    ```bash theme={"system"}
    export TILEBOX_API_KEY="YOUR_TILEBOX_API_KEY"
    ```

    Use a key with the smallest permissions needed for the task you want the agent to perform.
  </Step>

  <Step title="Verify the setup">
    Ask your agent to inspect its Tilebox capabilities before assigning a larger task.

    <AgentPrompt>
      Check your Tilebox setup. Confirm whether the `tilebox` CLI is installed, whether you can inspect commands with `tilebox agent-context`, which Tilebox skills are available, and which datasets are available. Do not modify any Tilebox resources.
    </AgentPrompt>
  </Step>
</Steps>

## Next steps

Learn how to [Iterate on Workflow Releases with Agents](/guides/workflows/agentic-workflow-iteration), or check out the [CLI Reference](/agents-and-ai-tools/tilebox-cli) to get an overview of useful `tilebox` terminal commands.