AOHP：一個開源的作業系統層級代理框架，用於個人化、高效且安全的互動

摘要

AI代理正驅動著一種新的軟體典範，能夠自主呼叫工具、提取資訊、管理記憶體，並完成跨應用程式與資料來源的任務。然而，現有的大多數終端使用者作業系統是為以應用為中心的工作流程所設計，對AI代理提供的原生支援相當有限。此一落差限制了代理的廣泛採用，並在傳統系統上執行代理時帶來執行開銷與安全風險。儘管代理原生作業系統的概念正在興起，但研究社群仍缺乏一個開放的測試平台，以探索代理中介互動所需的架構基元。我們提出AOHP（Android Open Harness Project），這是一個建立在Android開放原始碼專案（AOSP）之上的作業系統層級代理框架。AOHP的核心設計原則是將代理視為一級作業系統參與者，從而實現自適應使用者介面與有利於代理的執行環境。AOHP保留了成熟的Android軟硬體生態系統，同時引入了三項面向代理的系統機制：個人化服務組合、高效代理介面，以及安全資訊流。根據針對涵蓋作業系統代理關鍵能力的挑戰性任務所進行的初步實驗，AOHP在任務完成（完成率提升+21.12%）、執行成本（代幣成本降低-51.55%）以及安全策略合規方面展現出明顯優勢。

English

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.