arXiv AI
SkillForgeBench: Evaluating Agent Reliability Grounded in Agent Skill Specifications
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An Empirical Study of Agent Skills' Downstream Utility
arXiv:2610.08875v1 Announce Type: cross Abstract: Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studie...
arXiv Computation and Language
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Interlock: From Local Correctness to Task Completion in Long-Horizon Agents
Interlock is a framework that transforms long‑horizon tasks into typed completion graphs, linking evidence, decisions, and required effects through grounding, coupling, and realization edges. It compiles these graphs into a resettable workspace, a public request, and an evaluation rubric, and uses source‑coverage, public‑input, and agent‑as‑judge reviews to ensure that all mandatory requirements are met. Fine‑tuning Qwen3.6 backbones on Interlock‑generated trajectories improves pass rates on AutomationBench, JobBench, and Harvey LAB, showing that the synthesized experience benefits external task environments.
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An Empirical Study of Agent Skills' Downstream Utility
Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studies characterize Skill content and evaluate downstrea...
arXiv AI
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SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks
arXiv:2602. 12670v4 Announce Type: replace Abstract: Agent Skills are structured packages of procedural knowledge that augment large language model (LLM) agents at inference time.
arXiv Computation and Language
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SkillGym: Internalizing Human Skills into LLMs for Real-World Problem Solving
arXiv:2609.27717v1 Announce Type: new Abstract: Human-written agent skills encode rich workflows for real-world problem solving, but are typically used as external inference-time instructions rather...
arXiv AI
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A Framework for Evaluating Agentic Skills at Scale
arXiv:2606. 17819v1 Announce Type: cross Abstract: Agent skills -- structured, reusable knowledge artifacts that augment LLM agent capabilities -- have been rapidly adopted in industry, yet their cross-domain impact and use across commercial and open-source models remain under-studied, and no reusable methodology exists for evaluating an individual skill.