NAIM: A Canonical Data Format for AI-Assisted YANG Modeling

This document defines the NAIM (Natural AI Interface Modeling) Document format, a canonical JSON representation and a derived human- readable Markdown view designed to serve as a structured semantic intermediate representation between natural language descriptions and YANG data models [RFC7950]. NAIM addresses a recognized gap in the YANG authoring workflow: direct conversion from natural language to YANG is error-prone because essential modeling semantics — including configuration versus state distinction, list key identification, constraint expressions, operational preconditions, and cross-module relationships — are routinely absent or ambiguous in natural language input. NAIM makes these semantics explicit, structurally consistent, and machine- verifiable before YANG generation occurs. This document standardizes the canonical JSON structure, Markdown rendering rules, node template families, type representation, visibility and deviation declarations, and interoperability expectations for tools that produce and consume NAIM artifacts. It does not standardize AI model selection, prompt engineering strategies, dialogue policies, implementation-internal workflow logic, or runtime execution systems.