AOHP：一种开源的操作系统级代理平台，用于实现个性化、高效且安全的交互体验
AOHP: An Open-Source OS-Level Agent Harness for Personalized, Efficient and Secure Interaction
摘要
AI代理正在推动一种新的软件范式的发展。它们能够自主调用各种工具、提取信息、管理内存，并完成涉及不同应用程序和数据源的任务。然而，目前大多数现有的终端用户操作系统都是为以应用程序为中心的工作流程而设计的，对AI代理的支持非常有限。这种不匹配现象限制了AI代理的广泛应用，同时在传统系统上运行AI代理时还会带来执行成本较高以及安全风险等问题。虽然“原生AI代理操作系统”的概念正在逐渐发展，但研究界仍然缺乏一个合适的测试平台来探索实现AI代理交互所需的架构原理。我们提出了AOHP（Android Open Harness Project），这是一个基于Android开源项目构建的操作系统级别的AI代理框架。AOHP的核心设计理念是将AI代理视为具有同等地位的操作系统组件，从而能够实现自适应用户界面以及适合AI代理运行的运行时环境。AOHP保留了成熟的Android软件和硬件生态系统，同时引入了三种以AI代理为导向的系统机制：个性化服务组合、高效的AI代理界面以及安全的信息传输机制。根据针对一些具有挑战性的任务的初步实验结果来看，AOHP在任务完成率方面表现出显著优势（提升21.12%），执行成本也更低（降低51.55%的token成本），同时还能确保符合安全政策要求。
English Abstract
AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data sources. Most existing end-user operating systems, however, are designed for application-centric workflows and offer little native support for AI agents. This mismatch limits the wider adoption of agents and leads to execution overhead and safety risks when running agents on conventional systems. While the concept of agent-native operating systems is emerging, the research community lacks an open testbed to explore the architectural primitives desired for agent-mediated interaction. We present AOHP (Android Open Harness Project), an OS-level agent harness built on the Android Open Source Project (AOSP). The core design principle of AOHP is to treat agents as first-class OS actors, enabling adaptive user interfaces and agent-friendly runtime environments. AOHP preserves the mature Android software and hardware ecosystem while introducing three agent-oriented system mechanisms: personalized service composition, efficient agent interfaces, and secure information flow. Based on preliminary experiments on challenging tasks covering key capabilities of OS agents, AOHP shows clear advantages in task completion (+21.12% completion rate), execution cost (-51.55% token cost), and security-policy compliance.