SkillEval: A New Framework for Interpretable Evaluation of Agent Skills
A recent research article, 'SkillEval: Decomposing Agent Skill Quality into Interpretable Signals,' has been published on arXiv (ID: 2608.06891). This study tackles the issue of assessing the quality of agent skills, which are reusable components of procedural knowledge aiding agents in specialized tasks. The authors contend that current evaluation techniques, which often gauge skill quality through performance on specific downstream tasks, offer only a limited perspective. These methods indicate how well a skill aligns with a task but do not pinpoint areas needing enhancement. The paper introduces SkillEval, an interpretable framework for evaluating skills at the document level, assessing essential properties of the SKILL.md document with clear scoring directions to yield understandable scores. This framework also quantifies and mitigates the influence of these properties. The paper is classified as a new announcement and is accessible on arXiv.
Key facts
- Paper title: SkillEval: Decomposing Agent Skill Quality into Interpretable Signals
- arXiv ID: 2608.06891
- Announcement type: new
- Proposes SkillEval, an interpretable framework for document-level skill evaluation
- Focuses on general properties of the SKILL.md document
- Uses fixed and inspectable scoring directions for each property
- Existing evaluations measure skill quality via downstream task performance
- Downstream evaluation provides only a partial view of skill quality
Entities
Institutions
- arXiv