LLM Eval Harness Builder

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Designs evaluation harnesses for LLM applications, covering dataset construction, task-specific metrics, LLM-as-judge rubrics with bias controls, and regression gates. Helps teams measure quality, catch regressions across model or prompt changes, and report results with confidence intervals rather than vibes.

Варианты использования

  • Building an eval set and metrics for a RAG assistant
  • Designing an LLM-as-judge rubric with bias mitigations
  • Adding a regression gate for prompt and model changes in CI
  • Reporting eval results with statistical confidence

Пример промпта

We have a support chatbot backed by an LLM. Design an evaluation harness: propose an eval
dataset structure, define metrics for helpfulness/faithfulness/safety, write an LLM-as-judge
rubric that controls for position and verbosity bias, and outline a CI regression gate.

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Модальности

Вход: text, code
Выход: text, code

Похожие Skills

Автор

OpenModels Community

@openmodelsrun