Policy-as-Skill: Governed LLM Decision Support with Evidence, Deterministic Control, and Audit

Abstract:Organizations increasingly use LLMs for policy, compliance, risk, and operational decision support, requiring evidence validation, review routing, version control, and auditability. We introduce Policy-as-Skill (PaS), a modular runtime that packages these functions as executable, versioned policy capabilities. Thirteen methods are evaluated with a fixed Gemma4 backend on 600 development tasks. PaS+Audit achieves 53.8% exact accuracy, macro-F1 0.346, review F1 0.854, citation precision 1.000, policy-reference recall 0.984, and audit completeness 1.000, outperforming LLM+RAG on most governance and review metrics. Deterministic control raises aggregate accuracy to 61.2% but is strongly task dependent, supporting selective rather than universal rule-based intervention.

Artificial Intelligence (cs.AI); Symbolic Computation (cs.SC)

arXiv:2609.27087 [cs.AI]

(or arXiv:2609.27087v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.27087 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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