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Scorecard LLM Evals

by Scorecard

Build an evaluation project, define test cases and metrics, run models against them, read the results.

LLM Evaluation & Observability
Summary
Writing evals conversationally is the right use of this, because the bottleneck is test cases, not tooling.

Everyone agrees they should evaluate their prompts and nobody has enough test cases, because writing them is dull. Being able to describe a scenario and have the case land in the project removes the exact friction that keeps eval suites thin. Watch the loop though: an agent generating the cases that judge its own output is a closed circle worth breaking with a few cases written by a human who knows what failure looks like.

What it is

Scorecard's endpoint over their LLM evaluation platform — creating evaluation projects, configuring what is measured, and running it.

What you get
  • Evaluation projects, and test cases organised by scenario
  • Metric configuration such as accuracy and helpfulness
  • Running a model evaluation and reading the results
Requirements

OAuth. Their endpoint advertises protected-resource metadata, so a compliant client discovers the authorisation server itself. A local install is offered as an alternative.

Setup effort

Paste a URL, then authorize — add the endpoint to your client, then approve the OAuth consent screen