让人类与智能体协作可追溯、可审计，提升复杂任务的可信度。
Collaborative Human-Agent Protocol (CHAP)
- 设计结构化协议，将人类修改记录为带差分和理由的事件
- 实现跨团队协作中工作交接的可移植封装与不可否认审批
- 适合需要高可信度的金融、医疗、法律等关键领域部署
基础模型正从生成回应转向实际操作角色，需跨步骤规划、调用工具、请求人工输入、协调其他智能体，并对客户、代码、合同及临床决策负责。生产环境已不再是单人监督单一模型，而是跨越团队、时区与信任边界的多人多智能体协作。当前协作的技术规范仍不明确：当人类编辑智能体草案时，判断时刻是最宝贵信号，但常被记录在应用代码、聊天线程、工单评论和经验记忆中。现有标准MCP解决智能体访问工具与数据问题，A2A解决智能体间互操作，但均未定义人类与智能体共同完成可问责工作的共享工作空间。本文提出CHAP（协作人机协议），使原本消失于聊天中的覆盖操作变为携带差分、理由与内容哈希的结构化事件；轮班交接变为可携带的封包；人类对智能体草稿的批准成为可回放、不可否认的签名决策。协议通过核心组件（工作区、参与者、任务、成果物、追加式证据日志）与可组合的配置档（支持审查、模式、路由、协商、交接、身份、签名、透明审计）实现。规范、参考实现、一致性测试套件与示例已在GitHub公开：https://github.com/BrightbeamAI/chap
原文摘要 · Abstract (English)
Foundation models are moving from response generation into operational roles. They plan across steps, call tools, request human input, coordinate with other agents, and increasingly carry responsibility for work that affects customers, claims, code, contracts, and clinical decisions. Production deployments are no longer one human supervising one model. They are multi-human, multi-agent collaborations that cross teams, time zones, and trust boundaries. The technical surface for this collaboration remains weakly specified. When an agent drafts a response and a human edits it before it ships, the moment of human judgement is the most valuable signal in the system. In current practice it is recorded, if at all, in application code, chat threads, ticket comments, and tribal memory. Two protocol standards address adjacent concerns: MCP standardises agent access to tools and data, and A2A standardises agent-to-agent interoperability. Neither defines the shared workspace in which humans and agents perform accountable work together. This paper presents CHAP, the Collaborative Human-Agent Protocol. Under CHAP, the override that used to vanish into a chat thread becomes a structured event carrying a diff, a rationale, and a content hash. The handoff between shifts becomes a portable envelope rather than a pinned message. The human approval of an agent's draft becomes a non-repudiable signed decision that can be replayed years later. The protocol achieves this through a small Core (workspaces, participants, tasks, artefacts, and an append-only evidence log) together with composable profiles that add review, modes, routing, deliberation, handoff, identity, signatures, and transparency-backed audit as deployments require them. Specification, reference implementation, conformance suite, and worked examples are available at: https://github.com/BrightbeamAI/chap
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。