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

翻译：基础模型正从响应生成转向操作型角色。它们跨步骤规划、调用工具、请求人类输入、与其他智能体协调，并日益承担影响客户、索赔、代码、合同和临床决策的工作职责。生产部署已不再是单个人类监督单个模型，而是跨团队、跨时区、跨信任边界的多人类、多智能体协作。这种协作的技术规范仍显薄弱。当智能体起草响应并由人类在发布前编辑时，人类判断的瞬间成为系统中最有价值的信号。当前实践中，这种信号（若有记录）散落在应用代码、聊天线程、工单评论和隐性知识中。现有两项协议标准处理了相邻问题：MCP标准化了智能体对工具和数据的访问，A2A标准化了智能体间的互操作性。但两者均未定义人类与智能体共同履行问责工作的共享工作空间。本文提出CHAP协议（协作性人类-智能体协议）。在CHAP框架下，原本消失在聊天线程中的覆盖操作成为携带差异、理由和内容哈希的结构化事件；轮班交接变为便携式信封而非固定消息；人类对智能体草稿的批准成为不可否认的签名决策，可供多年后回放。该协议通过微内核（工作空间、参与者、任务、产物及仅可追加的证据日志）与可组合配置文件实现：配置文件根据部署需求添加审查、模式、路由、审议、交接、身份、签名及透明度支撑的审计功能。规范、参考实现、合规测试套件及工作示例详见：https://github.com/BrightbeamAI/chap