对话系统与模型协议融合，用结构化规范提升大模型可解释性。
The Convergence of Schema-Guided Dialogue Systems and the Model Context Protocol
- 以语义完整为核心，设计可约束、可推理的工具调用规范
- 提出五项设计原则，解决失败模式与工具间关系缺失问题
- 适合构建可审计的大模型应用，尤其关注生产环境部署
本文揭示了：基于模式的对话系统（SGD）与模型上下文协议（MCP）本质是同一范式在不同场景下的体现，均依赖模式编码工具签名、操作约束与推理引导。通过分析两者融合，提炼出五项基础设计原则：(1) 语义完整性优于语法精确性，(2) 显式定义动作边界，(3) 记录失败模式，(4) 兼容渐进披露，(5) 声明工具间关系。由此发现三大新洞察：首先，SGD原始设计合理，应被MCP继承；其次，两者均未充分挖掘失败模式与工具关联，本文予以补全；第三，渐进披露在真实令牌限制下成为关键扩展策略。论文提供每项原则的具体设计模式，使基于模式的治理成为无需访问专有系统即可实现的可扩展AI监管机制——这正是软件3.0的核心诉求。
原文摘要 · Abstract (English)
This paper establishes a fundamental convergence: Schema-Guided Dialogue (SGD) and the Model Context Protocol (MCP) represent two manifestations of a unified paradigm for deterministic, auditable LLM-agent interaction. SGD, designed for dialogue-based API discovery (2019), and MCP, now the de facto standard for LLM-tool integration, share the same core insight -- that schemas can encode not just tool signatures but operational constraints and reasoning guidance. By analyzing this convergence, we extract five foundational principles for schema design: (1) Semantic Completeness over Syntactic Precision, (2) Explicit Action Boundaries, (3) Failure Mode Documentation, (4) Progressive Disclosure Compatibility, and (5) Inter-Tool Relationship Declaration. These principles reveal three novel insights: first, SGD's original design was fundamentally sound and should be inherited by MCP; second, both frameworks leave failure modes and inter-tool relationships unexploited -- gaps we identify and resolve; third, progressive disclosure emerges as a critical production-scaling insight under real-world token constraints. We provide concrete design patterns for each principle. These principles position schema-driven governance as a scalable mechanism for AI system oversight without requiring proprietary system inspection -- central to Software 3.0.
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