prompt-evaluation-and-tuning

You set up CI regression testing for prompt engineering by configuring a declarative promptfoo pipeline that automatically evaluates prompt behavior against a matrix of tests. This framework validates prompts with blank-slate subagents and generates artifact documentation including traces and evidence.

Empirical subagent validation is a prompt evaluation method that runs prompts against blank-slate subagents to measure requirement achievement. It enables data-driven improvements by reducing bias and hidden errors in instruction design.

Yes, you can use promptfoo with CI-CD pipelines to test prompts automatically. The framework sets up a declarative CI regression pipeline that evaluates prompt behavior against a matrix of tests, ensuring reproducible testing and structured evaluation.

You evaluate prompts for subagents in Hermes workflows by applying empirical subagent validation and declarative CI testing. This involves dispatching blank-slate subagents to measure requirement achievement and running promptfoo pipelines for regression testing.

Yes, prompt evaluation works with AGENTS.md and CLAUDE.md files. The framework provides reusable guidance that applies prompt quality validation and regression testing to these files, ensuring consistent instruction correctness across teams.

The best way to prevent hidden errors in prompt design is to use empirical subagent validation and automated CI regression testing. This framework brings rigor to prompt design by reducing bias and validating instruction correctness with blank-slate subagents.