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papersSEP 10 04:00 UTC

Paper Compares Subagents and Agent Skills for Long-Horizon Agentic Tasks

A new arXiv paper investigates how language model agents can draw on libraries of reusable knowledge when tackling long-horizon tasks. It contrasts two approaches—subagents and agent skills, where skills are packaged as multi-file bundles—and examines which executes such knowledge more effectively. The study was announced in the cs.AI category and cross-listed in cs.CL and cs.LG.

arXiv agent-skills cs.AI language-model agents long-horizon tasks subagents

COVERAGE · 3 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.AISubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks ↗SEP 10 04:00 UTC

arXiv cs.CLSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks ↗SEP 10 04:00 UTC

arXiv cs.LGSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks ↗SEP 10 04:00 UTC