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

# Ingestion Quickstart

> Upload your data to Docent

This section will help you upload your data to Docent. We recommend using the Docent plugin with a coding agent to ingest logs after you run an evaluation. You can also [trace your agents](/ingestion/tracing) to capture data as they run.

## Instructions

1. **[Install the Docent plugin](/installation).** The `/docent` command below comes from the plugin.
2. **Read the [Data Models Overview](/concepts/overview)** to understand Docent's core abstractions (collections, agent runs, transcripts, metadata) so you can better instruct your coding agent on how you'd like your data organized.
3. **Point your coding agent at a directory containing your trajectories.** For best results, sort your trajectories by format before invoking the agent, and ingest one format at a time.

```text wrap theme={null}
/docent Ingest the trajectories at <PATH_TO_DATA>
```

## Notes

* Find [best practices](/ingestion/agentic#best-practices) for ingesting your data in our agentic ingestion guide.
* Using Inspect, Harbor, or NeMo-Gym? The [integration guides](/ingestion/integrations/inspect) handle those formats directly.
* You can read more about the [Python SDK](/ingestion/sdk) that our plugin writes under the hood if you want to write a script by hand, understand what your agent produced, or correct an existing ingestion script.

## Next steps

<Card title="Run your first analysis on sample data" icon="rocket" href="/analysis/quickstart" horizontal>
  Walk through a sample analysis on Terminal-Bench data and learn the core workflows.
</Card>