A Framework for Evaluating Agentic Skills at Scale
Agent skills -- structured, reusable knowledge artifacts that augment LLM agent capabilities -- have been rapidly adopted in industry, yet their cross-domain impact and use across commercial and open-source models remain under-studied, and no reusable methodology exists for evaluating an individual skill. In this work, we present an evaluation framework that lets a skill author construct realistic tasks to rigorously assess the aspects of a skill that matter most to them, and that estimates skill utility by solving those tasks. Further, we apply our evaluation approach at scale to 500 real-world skills, generating 1,000 tasks derived from the skills' content, along with instruction-follow...
| Authors | Maksim Shaposhnikov, Nicolas Fortuin, Simon Stipcich et al. |
|---|---|
| Primary category | cs.SE |
| Published | 16 June 2026 |
| Last updated at source | 16 June 2026 |
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