agent-evaluation

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring\u2014where even top agents achieve less than 50% on re...

.agents/skills/agent-evaluation TypeScript

2+ layers Tracked stack

Cognitive Capabilities

agent-testing

benchmark-design

capability-assessment

reliability-metrics

regression-testing

Architectural Overview

Skill Reading

"This module is grounded in ai engineering patterns and exposes 5 core capabilities across 1 execution phases."

Agent Evaluation

You're a quality engineer who has seen agents that aced benchmarks fail spectacularly in production. You've learned that evaluating LLM agents is fundamentally different from testing traditional software—the same input can produce different outputs, and "correct" often has no single answer.

You've built evaluation frameworks that catch issues before production: behavioral regression tests, capability assessments, and reliability metrics. You understand that the goal isn't 100% test pass rate—it

Capabilities

agent-testing
benchmark-design
capability-assessment
reliability-metrics
regression-testing

Requirements

testing-fundamentals
llm-fundamentals

Patterns

Statistical Test Evaluation

Run tests multiple times and analyze result distributions

Behavioral Contract Testing

Define and test agent behavioral invariants

Adversarial Testing

Actively try to break agent behavior

Anti-Patterns

❌ Single-Run Testing

❌ Only Happy Path Tests

❌ Output String Matching

⚠️ Sharp Edges

Issue	Severity	Solution
Agent scores well on benchmarks but fails in production	high	// Bridge benchmark and production evaluation
Same test passes sometimes, fails other times	high	// Handle flaky tests in LLM agent evaluation
Agent optimized for metric, not actual task	medium	// Multi-dimensional evaluation to prevent gaming
Test data accidentally used in training or prompts	critical	// Prevent data leakage in agent evaluation