🛰️ Daily AI Frontier
‹ back to 2026-08-06

Skill-Use: Can LLMs Actually Use Skills in Agentic Harnesses?

arXiv cs.CL LLM Agents Jinyi Han, Yuanjian Xu, Ying Liao, Xinyi Wang, Zishang Jiang, Zixiang Di, Fanyang Lu, Zhichao Hu, Yanghua Xiao 2026-08-05
Representative image for Skill-Use: Can LLMs Actually Use Skills in Agentic Harnesses?

TL;DR - Skill-Use is a benchmark testing whether LLM agents can autonomously recognize, retrieve, and follow "skills" (structured procedure documents) under progressive disclosure; it finds current agents unreliable, with the best configuration scoring only 0.613 SU.

  • Decomposes skill use into three facets: Trigger (invokes the relevant skill), Compliance (follows the prescribed procedure), and Boundary (avoids forbidden operations); the combined SU score credits execution only after triggering.
  • Benchmark scope: 79 real skills paired with 177 executable tasks across nine domains, grounded in real files, run in isolated Docker sandboxes and graded by a trajectory-based rubric.
  • Evaluated eight LLMs under two agent harnesses; triggering and procedural compliance emerged as independent bottlenecks rather than a single failure mode.
  • Both absolute scores and model rankings shifted with the harness, implying skill use is a harness-conditioned capability, not a fixed model property — so harness choice must be reported in agent evaluations.

view merged work →