arXiv AI

SkillSpec: Intent-Masked Specification Reasoning for Agent Skill Correctness

Hugging Face Trending Papers
Aug 18

TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation

TRUSS is a framework that generates and verifies automated agent skills, ensuring they are both functionally effective and safe. It first checks functional claims against evidence and evaluates artifacts against nine safety properties, then tests admitted skills in a controlled environment to capture execution traces and identify failures. The approach achieves perfect precision and recall in vulnerability detection, significantly reduces attack success rates, and boosts task effectiveness and security rates in skill generation benchmarks.

arXiv AI
Aug 19

TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation

TRUSS is a framework that generates and verifies automated agent skills, ensuring they are both functionally effective and safe. It evaluates candidate skills against source evidence and nine safety properties, then tests them in a controlled environment to capture execution traces and identify failures. The system iteratively refines skills based on these results, achieving high precision in vulnerability detection and significantly improving task performance and security rates.

By Zhibo Zhang, Zhen Ouyang, Ling Shi, Kailong Wang
arXiv AI
Aug 25

SkillAlchemy: Open-World Agent Skill Creation

arXiv:2608.23417v1 Announce Type: new Abstract: Agent skills are reusable procedural artifacts that extend language agents with specialized workflows, tool conventions, and domain behaviors at infere...

By Hengjun Wang, Shuyue Wei, Boyi Liu, Jun Yang, Yongxin Tong
arXiv AI
Jun 9

Anything2Skill: Compiling External Knowledge into Reusable Skills for Agents

arXiv:2606. 09316v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enables agents to access external knowledge at inference time, but it primarily retrieves fragmented declarative evidence, leaving agents to repeatedly infer task procedures from passages, manuals, examples, logs, or trajectories.

By Qianjun Pan, Yutao Yang, Junsong Li, Jie Zhou, Kai Chen, Xin Li, Qin Chen, Liang He
arXiv AI
Jul 24

Workflow-Localized Mechanism Learning: Attribution-Guided Repair and Knowledge Reuse for Structured Agent Skills

arXiv:2607. 20999v1 Announce Type: new Abstract: Agent Skills package reusable procedural knowledge as external artifacts for frozen language-model agents, yet existing optimizers do not jointly resolve where a failure occurs in a workflow, which mechanism caused it, and how relevant knowledge from third-party Skills should be reused locally.

By Zibin Lin, Shengli Zhang, Taotao Wang, Yihan Xia, Deen Ma, Guofu Liao