# Agent Testing and Benchmarks

Tests and benchmarks LLM agents for behavior, capability, reliability, and monitoring.

- Repository: https://github.com/davila7/claude-code-templates (33041 stars)
- Category: Testing
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add davila7/claude-code-templates --skill agent-evaluation -g -a claude-code -y`
Codex: `npx skills add davila7/claude-code-templates --skill agent-evaluation -g -a codex -y`
Cursor: `npx skills add davila7/claude-code-templates --skill agent-evaluation -g -a cursor -y`
Gemini CLI: `npx skills add davila7/claude-code-templates --skill agent-evaluation -g -a gemini-cli -y`

## Description

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring, where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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 |

## Related Skills

Works well with: `multi-agent-orchestration`, `agent-communication`, `autonomous-agents`