Prompt engineering has become a production critical component of generative AI systems. However, organizations still lack a shared, auditable method to qualify prompt assets against operational objectives, safety constraints, and compliance requirements. This paper introduces Prompt Readiness Levels (PRL), a nine level maturity scale inspired by TRL, and the Prompt Readiness Score (PRS), a multidimensional scoring method with gating thresholds designed to prevent weak link failure modes. PRL/PRS provide an original, structured and methodological framework for governing prompt assets specification, testing, traceability, security evaluation, and deployment readiness enabling valuation of prompt engineering through reproducible qualification decisions across teams and industries.

翻译：提示工程已成为生成式人工智能系统中生产关键组件。然而，各组织仍缺乏一种可共享、可审计的方法来根据运营目标、安全约束和合规要求对提示资产进行资格认证。本文提出了受技术准备度等级（TRL）启发的九级成熟度标度——提示准备度等级（PRL），以及提示准备度评分（PRS）——一种具有门限阈值的多维评分方法，旨在防止薄弱环节失效模式。PRL/PRS为提示资产的规范制定、测试、可追溯性、安全评估和部署就绪度管理提供了一个原创性、结构化、方法论化的框架，通过跨团队和跨行业可复现的资格决策实现提示工程的价值评估。