Source record

Published by LangChain Blog (T1.5 source). The original is at https://www.langchain.com/blog/how-similarweb-evaluates-long-form-agent-research-reports-with-langsmith.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Similarweb describes how it uses LangSmith to evaluate long-form agent research reports for its Data Studio product. The setup combines rubric-based scoring, faithfulness checks, trace inspection, and baseline comparisons to detect regressions such as dropped citations or over-reliance on a single data source.

Concrete evaluation stack for long-form agent outputs: rubrics, faithfulness checks, traces, baselines. A working pattern for anyone shipping agents that write reports.

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