Agent Performance Evaluation FAQs

Question 1

Can I use this skill to test RAG and context engineering?

Accepted Answer

Yes, it specifically includes methods for testing how different context strategies and window sizes affect agent performance, helping you identify performance 'cliffs' and optimization opportunities.

Question 2

What dimensions are used to score agent quality?

Accepted Answer

The skill suggests multi-dimensional scoring including factual accuracy, completeness, citation accuracy, source quality, and tool usage efficiency.

Question 3

What is the 'LLM-as-judge' approach included in this skill?

Accepted Answer

It involves using a highly capable language model (like Claude 3.5 Sonnet) to evaluate the outputs of other agents based on structured rubrics, providing scalable and consistent qualitative feedback.

Question 4

How does this skill handle non-deterministic agent behavior?

Accepted Answer

It implements outcome-focused evaluation methodologies that judge the final result and process reasonableness rather than requiring a specific, identical execution path for every run.

Question 5

How do token budgets affect agent evaluation?

Accepted Answer

Based on research like BrowseComp, token usage explains 80% of performance variance. This skill helps you evaluate agents under realistic token constraints to ensure production viability.

Agent Performance Evaluation

Key Features

Use Cases

Agent Performance Evaluation

Key Features

Use Cases