How does this skill handle flaky tests in AI agents?

It implements statistical test evaluation patterns that run tests multiple times to analyze result distributions, providing a more accurate picture of reliability than a single run.

What is behavioral contract testing for agents?

It involves defining specific invariants—rules or logic that the agent must always follow—and testing against those requirements regardless of the specific phrasing the LLM uses.

Why is agent evaluation different from traditional software testing?

LLM agents are non-deterministic, meaning the same input can produce different outputs. This skill uses statistical analysis and behavioral contracts rather than simple pass/fail string matching.

Can this skill prevent data leakage in evaluations?

Yes, it includes guidelines and 'sharp edges' warnings specifically designed to ensure test data isn't accidentally included in the agent's prompts or training data.

Agent Evaluation

Name: Agent Evaluation
Author: claudiodearaujo

byclaudiodearaujo

보안 및 테스팅

Evaluates and benchmarks LLM agents using behavioral testing, reliability metrics, and adversarial strategies to ensure production readiness.

소개

This skill provides a comprehensive framework for testing and validating LLM agents, addressing the unique challenges of non-deterministic AI behavior. It enables developers to move beyond simple string matching by implementing behavioral contract testing, statistical evaluation patterns, and multi-dimensional reliability metrics. By bridging the gap between laboratory benchmarks and real-world performance, this skill helps identify issues like metric gaming, data leakage, and regression failures before they reach production environments.

주요 기능

Multi-dimensional reliability and capability metrics
Adversarial testing to identify and fix edge-case vulnerabilities
Regression testing suites to prevent performance degradation
Behavioral contract testing for verifying agent invariants
Statistical evaluation patterns for non-deterministic outputs
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사용 사례

Benchmarking different LLM models for specific agentic workflows
Diagnosing and fixing flaky agent behaviors in complex multi-step tasks
Validating autonomous agent logic before production deployment

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claudiodearaujo/izacenter agent-evaluation

For use in Claude.ai and ChatGPT

Download Skill

GitHub

소개