Agent Evaluation Workbench

I built Agent Evaluation Workbench to design evaluation scenarios, generate and vary prompts, collect agent responses and review results in one workflow.

Design and run evaluations

Evaluations start with scenarios and criteria that define what to test and how to assess the responses. The workbench supports prompt generation and perturbation, response collection from a target agent, and scoring through deterministic checks and LLM judges.

Technical failures, refusals and substantive responses follow different evaluation paths, with individual flags and explanations retained alongside the scores.

1. 01Cases & criteria
2. 02Prompts & responses
3. 03Rules & LLM judges
4. 04Review & comparison

Inspect and compare results

The interface brings together individual responses, evaluation dimensions and comparisons between runs. Reviewers can move from aggregate scores to the cases behind them and inspect the criteria and judgments that produced each result.

Model-call observability connects results to their prompts, conversations and evaluation runs, helping reviewers investigate failures and understand what changed between tests.