> For the complete documentation index, see [llms.txt](https://docs.layerlens.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.layerlens.ai/more-in-this-section-5/build-trace-set.md).

# Build a trace set for agentic evals

1. Identify representative inputs (happy paths, edge cases, known-bad).
2. Run your agent against each; capture as a trace.
3. Tag and group them into a **dataset** (a named, versioned trace set).
4. Use the dataset as input to agentic evaluation.

## No traces yet? Generate them

You don't need production traffic to build a trace set. From **Catalog → Datasets → New Dataset → Generate synthetic traces**, produce a realistic multi-agent dataset from a built-in industry scenario (or by varying a few real traces) in minutes, then evaluate it like any other dataset. See [Synthetic data](/7.-observe-see-whats-happening/synthetic-data.md).

## See also

* [Datasets](/7.-observe-see-whats-happening/datasets.md)
* [Synthetic data](/7.-observe-see-whats-happening/synthetic-data.md)
* [Concept: Agentic evaluation](/8.-evaluate-score-the-outputs/agentic-evaluation.md)
* [Industry pattern: insurance missed escalation](/4.2-industry-use-cases/pattern-3.md)


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