发表机构
Google LLC; Purdue University（谷歌有限责任公司; 普渡大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文为智能体技能生态建立统一系统基础与参考架构，界定其九阶段生命周期，探讨安全威胁与防御机制，分类多领域系统实现，确立智能体技能为自主语言智能体的基础范式。
AI 中文摘要
自主大语言模型（LLM）智能体在复杂、长周期任务部署中日益面临可靠性、上下文消耗与执行稳定性瓶颈。整体式提示工程与无状态工具调用范式难以扩展，该领域正快速向「智能体技能」收敛：将执行知识外部化为可复用、可执行、可移植工件的模块化过程抽象。本文为智能体技能生态系统建立统一系统基础与参考架构，将技能形式化为连接高层认知规划与确定性执行环境的外部化过程知识，系统界定架构的九阶段生命周期：自主发现、创作与表示格式、内存存储、动态检索与路由、组合与编排、执行与修复、终身适应、实证评估及安全治理。本文还探讨市场动态、公共注册表、新兴对抗威胁向量，以及运行时验证与防御机制，同时对软件工程、操作系统导航、具身机器人学与科学发现领域的系统实现进行分类，并强调持续学习与基准真实性方面的关键开放挑战。本工作确立智能体技能为构建可扩展、鲁棒且可验证的自主语言智能体的基础范式。
英文摘要
Autonomous large language model (LLM) agents increasingly face reliability, context consumption, and execution stability bottlenecks when deployed on complex, long-horizon tasks. While monolithic prompt engineering and stateless tool-calling paradigms struggle to scale, the field is rapidly converging toward \emph{agentic skills}: modular procedural abstractions that externalize execution knowledge into reusable, executable, and portable artifacts. This paper establishes a unified systems foundation and reference architecture for the agentic skills ecosystem. We formalize skills as externalized procedural knowledge bridging high-level cognitive planning with deterministic execution environments, and systematically delineate the architecture across a nine-stage lifecycle: autonomous discovery, authoring and representation formats, memory storage, dynamic retrieval and routing, composition and orchestration, execution and repair, lifelong adaptation, empirical evaluation, and security governance. We further examine marketplace dynamics, public registries, and emerging adversarial threat vectors, alongside runtime verification and defense mechanisms. Finally, we categorize system implementations across software engineering, operating system navigation, embodied robotics, and scientific discovery, while highlighting critical open challenges in continual learning and benchmark realism. This work establishes agentic skills as a foundational paradigm for building scalable, robust, and verifiable autonomous language agents.
