Testing Agent Skills Systematically with Evals | OpenAI Developers

What this post added

This post introduces a systematic approach to testing and evaluating agent skills, particularly within the context of Codex. It details how to define success metrics before skill development, create skills with clear names and descriptions, manually trigger skills to uncover assumptions, and use small, targeted prompt sets for regression testing. The core contribution is the methodology for using Evals, which involves defining outcome, process, and style goals, and implementing lightweight deterministic graders and rubric-based scoring to ensure skill reliability and consistency.