<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.c4tz-marc" target="https://datatracker.ietf.org/doc/html/draft-c4tz-marc-02">
   <front>
      <title>MARC: A Control and Uncertainty Disclosure Profile for Generative Models and Agents</title>
      <author initials="" surname="c4tz" fullname="c4tz">
         <organization>c0dx3</organization>
      </author>
      <date month="May" day="3" year="2026" />
      <abstract>
	 <t>   This document specifies MARC, a vendor-neutral control and
   uncertainty-disclosure profile for generative models and agentic
   systems.  MARC defines a small set of interoperable control metadata,
   separates pre-decision capability assessment from post-decision
   answer confidence, identifies the target of confidence disclosures,
   and defines a bounded primary action set for answering,
   clarification, retrieval, tool use, additional deliberation,
   abstention, and escalation.

   MARC does not standardize model internals, training methods, agent
   discovery, authorization, transport, tool schemas, provenance
   systems, or claims about machine cognition.  Instead, it defines
   externally observable semantics that can be implemented by model
   providers, orchestration layers, evaluation harnesses, API gateways,
   and user-facing systems.  The goal is to reduce silent failure,
   unnecessary externalization, and misleading uncertainty communication
   while improving auditability and interoperability.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-c4tz-marc-02" />
   
</reference>
