> ## Documentation Index
> Fetch the complete documentation index at: https://overmind-b84ae13c-codex-workshop-queue-capacity.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Sign up or self-host, paste one prompt into your coding agent, then improve the agent with /overmind commands.

Overmind onboards through your coding agent. Cursor, Claude Code, OpenCode and Codex all work: one pasted prompt installs the SDK, connects the MCP server and scans your repository into capabilities. After that, instrumentation, datasets, training and optimisation run from the same chat.

<Steps>
  <Step title="Open the Console">
    Sign up at [console.overmindlab.ai](https://console.overmindlab.ai), or open your own Console, for example `http://localhost:5173` — see [Self-hosting](/platform/self-hosting). A **project** holds your capabilities, traces, datasets, runs, models and keys; the first sync creates it.
  </Step>

  <Step title="Copy the onboarding prompt">
    On the **Agent** page, pick **Cursor**, **Claude Code**, **OpenCode** or **Codex**, then select **Copy onboarding prompt**. The prompt carries a temporary account key, so paste it only into your local coding agent. **Manual setup** shows the same commands for a terminal.
  </Step>

  <Step title="Paste it into your coding agent">
    Open the repository root as the workspace and paste the prompt. The agent installs `overmind`, runs `overmind init` and `overmind sync`, and saves a project-scoped key to `.overmind/credentials.toml`. Reload the agent once so it loads the Overmind MCP server; in Claude Code, exit and run `claude -c`.

    The agent then scans the repository into [capabilities](/core/capabilities#the-scan) and syncs them to the Console. To regroup capabilities or change their evals, ask the agent.
  </Step>

  <Step title="Improve the agent with /overmind commands">
    Each command drives one loop end to end. Cursor and Claude Code take them as slash commands; in OpenCode and Codex, ask for the step by name.

    | Command | What it does |
    | - | - |
    | `/overmind ensure-tracing` | Instrument the code and check that traces arrive |
    | `/overmind dataset` | Build, clean, upload or export a dataset |
    | `/overmind finetune` | Fine-tune, deploy and smoke-test a model |
    | `/overmind optimise` | Run prompt and code optimisation |
    | `/overmind backtest` | Compare models in the repository |

    Plain `/overmind` routes to the right workflow when you describe the goal instead.
  </Step>

  <Step title="Watch it land in the Console">
    Once traces arrive, open **Observability**. **Task executions** shows one row per scored unit of work, **Root traces** one row per trace, and **Sessions** groups traces by session.

    <Frame caption="Task executions: one row per scored unit, with the task it bound to and its execution score.">
      <img src="https://mintcdn.com/overmind-b84ae13c-codex-workshop-queue-capacity/qKX7fWUX8kgqFDpP/images/platform/observability-executions.jpg?fit=max&auto=format&n=qKX7fWUX8kgqFDpP&q=85&s=f0e02bde45d4e9c62bf620c52a74f5cb" alt="Observability task executions view in the Overmind console" width="1456" height="821" data-path="images/platform/observability-executions.jpg" />
    </Frame>
  </Step>
</Steps>

Deployed processes need `OVERMIND_API_KEY` in their runtime configuration; the saved project key covers local runs only. Not using Python or a coding agent? Any OpenTelemetry SDK can export to the [OTLP endpoint](/core/observability#the-otlp-endpoint).

## Next steps

<CardGroup cols={2}>
  <Card title="Structure your traces" href="/tracing/sdk-python">
    Bracket each run with `overmind.run()` and add `@tool` and `@observe` spans so traces mirror your agent's real control flow.
  </Card>

  <Card title="Read the pushed capabilities" href="/core/capabilities">
    What sync uploaded: capabilities, prompts, tools, behaviours, and the trajectory map.
  </Card>

  <Card title="Build a dataset from traces" href="/core/datasets">
    Select traces and land them as an eval or training dataset with provenance intact.
  </Card>

  <Card title="Work through MCP" href="/platform/mcp">
    The tool catalog your coding agent already has after onboarding.
  </Card>
</CardGroup>


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