Paper deep dive
Prompt Readiness Levels (PRL): a maturity scale and scoring framework for production grade prompt assets
Sebastien Guinard
Intelligence
Status: succeeded | Model: Gemma-4-26B-A4B | Prompt: intel-v1 | Confidence: 95%
Last extracted: 7/13/2026, 3:32:01 AM
Summary
The paper introduces Prompt Readiness Levels (PRL), a nine-level maturity scale, and the Prompt Readiness Score (PRS), a multidimensional scoring method, to provide a structured framework for governing, testing, and qualifying prompt assets in production-grade generative AI systems.
Entities (7)
Relation Signals (6)
Sebastien Guinard → affiliatedwith → University of Grenoble Alpes
confidence 99% · Sebastien Guinard (Univ. Grenoble Alpes
Sebastien Guinard → affiliatedwith → CEA
confidence 99% · Sebastien Guinard (Univ. Grenoble Alpes, CEA
Prompt Readiness Levels → publishedin → arXiv
confidence 99% · arXiv:2603.15044v1
Prompt Readiness Levels → isinspiredby → TRL
confidence 95% · a nine level maturity scale inspired by TRL
Prompt Readiness Levels → providesframeworkfor → governing prompt assets specification
confidence 95% · PRL/PRS provide an original, structured and methodological framework for governing prompt assets specification
Prompt Readiness Score → haspurpose → prevent weak link failure modes
confidence 90% · designed to prevent weak link failure modes
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Abstract
Abstract: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.
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- Source: https://arxiv.org/abs/2603.15044v1
- Canonical: https://arxiv.org/abs/2603.15044v1
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Skip to main content arXiv is now an independent nonprofit! Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Artificial Intelligence arXiv:2603.15044v1 (cs) [Submitted on 16 Mar 2026] Title:Prompt Readiness Levels (PRL): a maturity scale and scoring framework for production grade prompt assets Authors:Sebastien Guinard (Univ. Grenoble Alpes, CEA, DRT F-38000 Grenoble) View a PDF of the paper titled Prompt Readiness Levels (PRL): a maturity scale and scoring framework for production grade prompt assets, by Sebastien Guinard (Univ. Grenoble Alpes and 2 other authors View PDF Abstract: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. Comments: 7 pages, 1 figure Subjects: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG) ACM classes: I.2.0; I.2.6; I.2.7; I.2.11 Cite as: arXiv:2603.15044 [cs.AI] (or arXiv:2603.15044v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2603.15044 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Sebastien Guinard [view email] [v1] Mon, 16 Mar 2026 09:54:36 UTC (308 KB) Full-text links: Access Paper: View a PDF of the paper titled Prompt Readiness Levels (PRL): a maturity scale and scoring framework for production grade prompt assets, by Sebastien Guinard (Univ. Grenoble Alpes and 2 other authorsView PDF view license Current browse context: cs.AI < prev | next > new | recent | 2026-03 Change to browse by: cs cs.CY cs.LG References & Citations NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?) mathjaxToggle(); We gratefully acknowledge support from our major funders, member institutions, , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from