Practical Guide to Evaluating and Testing Agent Skills

This article by Philipp Schmid provides a practical guide for systematically testing and evaluating agent skills using a lightweight eval harness. It defines three dimensions of success — outcome correctness, style/instruction adherence, and efficiency — and walks through building a prompt set of 10-20 test cases, running agents through a CLI, and writing deterministic regex-based checks. The author demonstrates the approach using the Gemini Interactions API skill, improving its pass rate from 66.7% to 100% through iterative fixes, with the skill description rewrite alone fixing 5 of 7 failures. The guide also covers LLM-as-judge for qualitative checks and offers 10 best practices including negative tests, multiple trials, and detecting when a skill can be retired.

Source: Practical Guide to Evaluating and Testing Agent Skills