SkillJuror: Measuring How Agent Skill Organization Changes Runtime Behavior
📰 ArXiv cs.AI
Learn how SkillJuror measures the impact of agent skill organization on runtime behavior in large language models
Action Steps
- Implement Progressive Disclosure to organize agent skills
- Compare the performance of Progressive Disclosure with a normalized flat baseline
- Use SkillJuror framework to evaluate Skill writing paradigms
- Analyze the results to identify the most effective skill organization method
- Apply the findings to optimize agent skill organization and improve runtime behavior
Who Needs to Know This
Researchers and developers working with large language models and agent skills can benefit from understanding how skill organization affects runtime behavior, enabling them to optimize their models and improve performance
Key Insight
💡 The organization of agent skills can significantly impact runtime behavior in large language models
Share This
💡 SkillJuror helps measure how agent skill organization impacts runtime behavior in LLMs
Key Takeaways
Learn how SkillJuror measures the impact of agent skill organization on runtime behavior in large language models
Full Article
Title: SkillJuror: Measuring How Agent Skill Organization Changes Runtime Behavior
Abstract:
arXiv:2606.11543v1 Announce Type: new Abstract: Agent Skills augment large language model (LLM) agents with procedural knowledge at inference time, but current benchmarks rarely distinguish what a Skill says from how it is organized. We study this distinction through Progressive Disclosure, where a concise root file points agents to supporting resources on demand, and compare it with a normalized flat baseline. We present SkillJuror, a framework for evaluating Skill writing paradigms through sem
Abstract:
arXiv:2606.11543v1 Announce Type: new Abstract: Agent Skills augment large language model (LLM) agents with procedural knowledge at inference time, but current benchmarks rarely distinguish what a Skill says from how it is organized. We study this distinction through Progressive Disclosure, where a concise root file points agents to supporting resources on demand, and compare it with a normalized flat baseline. We present SkillJuror, a framework for evaluating Skill writing paradigms through sem
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