SkillEval: Decomposing Agent Skill Quality into Interpretable Signals
Agent skills provide reusable knowledge that helps agents solve specialized tasks. As their use expands, evaluating skill quality becomes increasingly important. Existing evaluations often measure skill quality based on improvements in agent performance on specific tasks. However, a reusable skill may apply across multiple scenarios. Evaluation on a single downstream task mainly reflects the compatibility between a skill and the evaluated task, provides only a partial view of skill quality, and does not identify which aspects need improvement. We find that general properties of the \texttt{SKILL.md} document play an important role in skill quality. To evaluate these properties, we propose...
| Authors | Jiahui Han, Qinuo Li, Ziheng Peng et al. |
|---|---|
| Primary category | cs.AI |
| Published | 7 August 2026 |
| Last updated at source | 12 October 2026 |
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