The transition from monolithic language models to modular, skill-equipped agents marks a defining shift in how large language models (LLMs) are deployed in practice. Rather than encoding all procedural knowledge within model weights, agent skills -- composable packages of instructions, code, and resources that agents load on demand -- enable dynamic capability extension without retraining. It is formalized in a paradigm of progressive disclosure, portable skill definitions, and integration with the Model Context Protocol (MCP). This survey provides a comprehensive treatment of the agent skills landscape, as it has rapidly evolved during the last few months. We organize the field along four axes: (i) architectural foundations, examining the SKILL$.$md specification, progressive context loading, and the complementary roles of skills and MCP; (ii) skill acquisition, covering reinforcement learning with skill libraries, autonomous skill discovery (SEAgent), and compositional skill synthesis; (iii) deployment at scale, including the computer-use agent (CUA) stack, GUI grounding advances, and benchmark progress on OSWorld and SWE-bench; and (iv) security, where recent empirical analyses reveal that 26.1% of community-contributed skills contain vulnerabilities, motivating our proposed Skill Trust and Lifecycle Governance Framework -- a four-tier, gate-based permission model that maps skill provenance to graduated deployment capabilities. We identify seven open challenges -- from cross-platform skill portability to capability-based permission models -- and propose a research agenda for realizing trustworthy, self-improving skill ecosystems. Unlike prior surveys that broadly cover LLM agents or tool use, this work focuses specifically on the emerging skill abstraction layer and its implications for the next generation of agentic systems. Project repo: https://github.com/scienceaix/agentskills
Shattered Compositionality: Counterintuitive Learning Dynamics of Transformers for Arithmetic
University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；Department of Computer Sciences, University of Wisconsin–Madison（威斯康星大学麦迪逊分校计算机科学系）；Department of Statistics, University of Wisconsin–Madison（威斯康星大学麦迪逊分校统计学系）
SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills
The Ohio State University（俄亥俄州立大学）；The University of Chicago（芝加哥大学）；University College London（伦敦大学学院）；University of Michigan（密歇根大学）；The Chinese University of Hong Kong（香港中文大学）；Case Western Reserve University（凯斯西储大学）；Amazon（亚马逊）
Can Agents Trust Their Skills? Uncovering Unsafe Chains of Trust in Skill-Based LLM Agents
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；Worcester Polytechnic Institute（伍斯特理工学院）；School of Cyberspace Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）
SkillsMetric: Mapping the Detection Boundary of Static Analysis for Malicious Agent Skills
The Graduate Center, City University of New York（纽约城市大学研究生中心）；Hunter College, City University of New York（纽约城市大学亨特学院）；The Ohio State University（俄亥俄州立大学）
DIRO & Institut Courtois, Université de Montréal（DIRO与Courtois研究所，蒙特利尔大学）；Mila – Québec AI Institute（魁北克人工智能研究所）；Microsoft Research（微软研究院）；Canada CIFAR AI Chair（加拿大CIFAR人工智能主席）
When Experience Becomes Instruction: Trajectory Poisoning in Self-Evolving Agent Skill Systems
Ant Group（蚂蚁集团）；Zhejiang University（浙江大学）；Tsinghua University（清华大学）；Hangzhou Dianzi University（杭州电子科技大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Xi’an Jiaotong University（西安交通大学）
"Do Not Mention This to the User": Detecting and Understanding Malicious Agent Skills in the Wild
Griffith University（格里菲斯大学）；Nanyang Technological University（南洋理工大学）；University of New South Wales（新南威尔士大学）；Zhejiang Key Laboratory of Digital Fashion and Data Governance, Zhejiang Sci-Tech University（浙江数字时尚与数据治理重点实验室，浙江科技大学）
How Your Credentials Are Leaked by LLM Agent Skills: An Empirical Study
Griffith University（格里菲斯大学）；Wake Forest University（威克森林大学）；Nanyang Technological University（南洋理工大学）；University of New South Wales（新南威尔士大学）；Zhejiang Sci-Tech University（浙江科技学院）；The University of Tokyo（东京大学）；University of Alberta（阿尔伯塔大学）；Independent Researcher（独立研究者）
SkillFlow: Scalable and Efficient Agent Skill Retrieval System
University of California, Davis（加州大学戴维斯分校）；USDA/NSF AI Institute for Next Generation Food Systems（美国农业部/国家科学基金会下一代食品系统人工智能研究所）；Process Integration and Predictive Analytics（过程集成与预测分析）
