llm-testing

What problem does it solve?

This Skill addresses the challenge of reliably evaluating and testing Large Language Models (LLMs), which are inherently probabilistic and subjective. It provides frameworks to ensure LLM outputs meet desired quality standards.

Core Features & Use Cases

• Evaluation Metrics: Implements standard metrics like BLEU, ROUGE-L, and semantic similarity for quantitative assessment.
• LLM-as-Judge: Leverages LLMs themselves to evaluate responses, enabling scalable quality checks.
• Regression & Safety Testing: Includes tools for behavioral testing, snapshotting, and red teaming to catch regressions and identify safety vulnerabilities.
• Use Case: A team developing a customer service chatbot can use this Skill to automatically test new model versions against a suite of prompts, ensuring that responses remain accurate, helpful, and safe, and that performance doesn't degrade over time.

Quick Start

Use the llm-testing skill to run regression tests on your model with the provided test suite.