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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.

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 to capture data as they run.

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Instructions

  1. Install the Docent plugin. The /docent command below comes from the plugin.
  2. Read the Data Models 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.
/docent Ingest the trajectories at <PATH_TO_DATA>

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Notes

  • Find best practices for ingesting your data in our agentic ingestion guide.
  • Using Inspect, Harbor, or NeMo-Gym? The integration guides handle those formats directly.
  • You can read more about the Python 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.

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Next steps

Run your first analysis on sample data

Walk through a sample analysis on Terminal-Bench data and learn the core workflows.