The increasing deployment of autonomous AI agents on the web is hampered by a fundamental misalignment: agents must infer affordances from human-oriented user interfaces, leading to brittle, inefficient, and insecure interactions. To address this, we introduce VOIX, a web-native framework that enables websites to expose reliable, auditable, and privacy-preserving capabilities for AI agents through simple, declarative HTML elements. VOIX introduces <tool> and <context> tags, allowing developers to explicitly define available actions and relevant state, thereby creating a clear, machine-readable contract for agent behavior. This approach shifts control to the website developer while preserving user privacy by disconnecting the conversational interactions from the website. We evaluated the framework's practicality, learnability, and expressiveness in a three-day hackathon study with 16 developers. The results demonstrate that participants, regardless of prior experience, were able to rapidly build diverse and functional agent-enabled web applications. Ultimately, this work provides a foundational mechanism for realizing the Agentic Web, enabling a future of seamless and secure human-AI collaboration on the web.

翻译：自主人工智能智能体在网络上的日益部署受到一个根本性错位的阻碍：智能体必须从面向人类的用户界面推断其可用功能，导致交互变得脆弱、低效且不安全。为解决这一问题，我们提出了VOIX，一种原生网络框架，使网站能够通过简单的声明式HTML元素为AI智能体提供可靠、可审计且保护隐私的能力。VOIX引入了<tool>和<context>标签，允许开发者明确定义可用操作和相关状态，从而为智能体行为创建清晰、机器可读的契约。这种方法将控制权转移给网站开发者，同时通过将对话交互与网站分离来保护用户隐私。我们在一项为期三天的黑客马拉松研究中，邀请了16名开发者，评估了该框架的实用性、易学性和表达能力。结果表明，无论参与者先前经验如何，都能快速构建多样化且功能完善的智能体赋能网络应用。最终，这项工作为实现智能体网络（Agentic Web）提供了基础机制，为未来网络上无缝、安全的人机协作奠定了基础。