How does this skill help with flaky agent tests?

It implements statistical test evaluation patterns that analyze result distributions across multiple runs to distinguish between systemic failures and expected variability.

Can this skill prevent agents from gaming benchmarks?

Yes, it utilizes multi-dimensional evaluation and adversarial testing to ensure agents are optimized for actual task completion rather than just hitting specific metric targets.

Why is LLM agent testing different from traditional software testing?

Unlike traditional software, agents are non-deterministic; the same input can yield different valid outputs, requiring statistical distribution analysis rather than simple string matching.

What is behavioral contract testing for agents?

It defines invariant behaviors that an agent must always exhibit, regardless of the specific response text, ensuring adherence to core operational constraints.

Agent Evaluation

Name: Agent Evaluation
Author: claudiodearaujo

byclaudiodearaujo

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보안 및 테스팅

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

The Agent Evaluation skill provides a robust framework for assessing the performance and reliability of AI agents, moving beyond simple string matching to address the inherent non-determinism of LLMs. It equips developers with methodologies for statistical evaluation, behavioral contract testing, and adversarial assessment to catch failures that traditional benchmarks often miss. By focusing on multi-dimensional metrics and production monitoring, this skill helps bridge the gap between laboratory benchmarks and real-world reliability, ensuring that autonomous agents perform consistently across varying edge cases.

주요 기능

01Statistical evaluation of non-deterministic result distributions

02Behavioral contract testing to define agent invariants

03Adversarial testing frameworks to identify edge-case failures

04Multi-dimensional capability assessment and benchmarking

05Production-grade reliability metrics and monitoring

061 GitHub stars

사용 사례

01Validating agent consistency before production deployment

02Benchmarking new LLM versions against existing agent workflows

03Identifying behavioral regressions in complex multi-agent systems

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claudiodearaujo/sistema-de-narra-o-de-livro agent-evaluation

For use in Claude.ai and ChatGPT

Download Skill